Journal Papers

[J-1]   F.M. Frattale Mascioli, A. Rizzi, M. Panella, and G. Martinelli, “Scale-Based Approach to Hierarchical Fuzzy Clustering”, Signal Processing, Vol. 80, No. 6, pp. 1001-1016, ISSN: 0165-1684, DOI: 10.1016/S0165-1684(00)00016-5, Elsevier Science B.V., The Netherlands, June 2000.

[J-2]   M. Panella and G. Martinelli, “RNS quasi-chaotic generators”, Electronics Letters, Vol. 36, No. 15, pp. 1325-1326, ISSN: 0013-5194, DOI: 10.1049/el:20000952, IEE, U.K., July 2000.

[J-3]   M. Panella and G. Martinelli, “RNS quasi-chaotic generator for self-correcting secure communication”, Electronics Letters, Vol. 37, No. 5, pp. 325-327, ISSN: 0013-5194, DOI: 10.1049/el:20010203, IEE, U.K., March 2001.

[J-4]   A. Rizzi, M. Panella, and F.M. Frattale Mascioli, “Adaptive Resolution Min-Max Classifiers”, IEEE Transactions on Neural Networks, Vol. 13, No. 2, pp. 402-414, ISSN: 1045-9227, DOI: 10.1109/72.991426, IEEE, U.S.A., March 2002.

[J-5]   M. Panella and G. Martinelli, “An RNS architecture for Quasi-Chaotic Oscillators”, The Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology, Vol. 33, No. 1-2, pp. 199-220, ISSN: 0922-5773, DOI: 10.1023/A:1021162422734, Kluwer Academic Publishers, The Netherlands, February 2003. 

[J-6]   M. Panella, A. Rizzi, and G. Martinelli, “Refining accuracy of environmental data prediction by MoG neural networks”, Neurocomputing, Vol. 55, No. 3-4, pp. 521-549, ISSN: 0925-2312, DOI: 10.1016/S0925-2312(03)00392-8, Elsevier B.V., The Netherlands, October 2003.

[J-7]   M. Panella, A. Rizzi, F.M. Frattale Mascioli, and G. Martinelli, “From Circuits to Neurofuzzy Networks: Synthesis by Numerical and Linguistic Information”, Journal of Circuits, Systems, and Computers, Vol. 13, No. 1, pp. 205-236, ISSN: 0218-1266, DOI: 10.1142/S0218126604001258, World Scientific Publishing Company, Singapore, 2004.

[J-8]   M. Panella and A.S. Gallo, “An Input-Output Clustering Approach to the Synthesis of ANFIS Networks”, IEEE Transactions on Fuzzy Systems, Vol. 13, No. 1, pp. 69-81, ISSN: 1063-6706, DOI: 10.1109/TFUZZ.2004.839659, IEEE, U.S.A., February 2005. 

[J-9]   M. Panella and G. Martinelli, “RC Distributed Circuits for Vibration Damping in Piezo-Electromechanical Beams”, IEEE Transactions on Circuits and Systems–II, Vol. 52, No. 8, pp. 486-490, ISSN: 1549-7747 (ex 1057-7130 su ISI/Scopus), DOI: 10.1109/TCSII.2005.848981, IEEE, U.S.A., August 2005.

[J-10]   M. Panella, M. Paschero, and F.M. Frattale Mascioli, “Optimised RC-active Synthesis of PEM Networks”, Electronics Letters, Vol. 41, No. 19, pp. 1041-1043, ISSN: 0013-5194, DOI: 10.1049/el:20051847, IEE, U.K., September 2005.

[J-11]   C. Mazzetti, F.M. Frattale Mascioli, F. Baldini, M. Panella, R. Risica, and R. Bartnikas, “Partial Discharge Pattern Recognition by Neuro-Fuzzy Networks in Heat-Shrinkable Joints and Terminations of XLPE Insulated Distribution Cables”, IEEE Transactions on Power Delivery, Vol. 21, No. 3, pp. 1035-1044, ISSN: 0885-8977, DOI: 10.1109/TPWRD.2006.875861, IEEE, U.S.A., July 2006. 

[J-12]   M. Paschero, M. Panella, and F.M. Frattale Mascioli, “Stability Analysis of Optimal PEM Networks”, Electronics Letters, Vol. 42, No. 17, pp. 961-962, ISSN: 0013-5194, DOI: 10.1049/el:20062114, IET, U.K., August 2006.

[J-13]   M. Panella and G. Martinelli, “Neurofuzzy Networks with Nonlinear Quantum Learning”, IEEE Transactions on Fuzzy Systems, Vol. 17, No. 3, pp. 698-710, ISSN: 1063-6706, DOI: 10.1109/TFUZZ.2008.928603, IEEE, U.S.A., June 2009.

[J-14]   M. Panella and G. Martinelli, “Neural Networks with Quantum Architecture and Quantum Learning”, International Journal of Circuit Theory and Applications, Vol. 39, No. 1, pp. 61-77, ISSN: 1097-007X, DOI: 10.1002/cta.619, John Wiley & Sons, Ltd., U.K., January 2011.

[J-15]   M. Panella, “Advances in biological time series prediction by neural networks”, Biomedical Signal Processing and Control, Vol. 6, No. 2, pp. 112-120, ISSN: 1746-8094, DOI: 10.1016/j.bspc.2010.09.006, Elsevier Ltd., U.K., April 2011.

[J-16]   M. Panella and L. Basset, “An Efficient GPU Implementation of Modified Discrete Cosine Transform Using CUDA”, International Journal of Computer Science and Information Security, Vol. 10, No. 5, Paper 30041269, pp. 23-30, ISSN: 1947-5500, IJCSIS Publication, Pittsburgh, PA, U.S.A., May 2012.

[J-17]   M. Panella and G. Martinelli, “The Quantum Approach Leading from Evolutionary to Exhaustive Optimization”, Journal of Applied Sciences, Vol. 12, No. 19, pp. 1995-2005, ISSN: 1812-5654, DOI: 10.3923/jas.2012.1995.2005, Asian Network for Scientific Information, U.S.A., September 2012.

[J-18]   M. Panella, “A Hierarchical Procedure for the Synthesis of ANFIS Networks”, Advances in Fuzzy Systems, Vol. 2012, Article ID 491237, pp. 1-12, ISSN: 1687-7101, DOI:10.1155/2012/491237, Hindawi Publishing Corporation, U.S.A., October 2012.

[J-19]   M. Panella, F. Barcellona, and R.L. D’Ecclesia, “Forecasting Energy Commodity Prices Using Neural Networks”, Advances in Decision Sciences, Vol. 2012, Article ID 289810, pp. 1-26, ISSN: 2090-3359, DOI: 10.1155/2012/289810, Hindawi Publishing Corporation, U.S.A., December 2012.

[J-20]   M. Maisto, M. Panella, L. Liparulo, and A. Proietti, “An Accurate Algorithm for the Identification of Fingertips Using an RGB-D Camera”, IEEE Journal on Emerging and Selected Topics in Circuits and Systems, Vol. 3, No. 2, pp. 272-283, ISSN: 2156-3357, DOI: 10.1109/JETCAS.2013.2256830, IEEE, U.S.A, June 2013.

[J-21]   A. Festa, M. Panella, R. Lo Sterzo, and L. Liparulo, “Radiofrequency Identification Systems for Healthcare: A Case Study on Electromagnetic Exposures”, Journal of Clinical Engineering, Vol. 38, No. 3, pp. 125-133, ISSN: 0363-8855, DOI: 10.1097/JCE.0b013e31829a9174, Lippincott Williams & Wilkins, U.S.A., July 2013.

[J-22]   M. Panella, R.L. D’Ecclesia, D.G. Stack, and F. Barcellona, “Crude oil prices and kernel-based models”, International Journal of Financial Engineering and Risk Management, Vol. 1, No. 3, pp. 214-238, ISSN: 2049-0909, DOI: 10.1504/IJFERM.2014.058761, Inderscience Publishers, Geneva, Switzerland, March 2014.

[J-23]   M. Panella, A. Festa, and R. Lo Sterzo, “Analisi dell’impatto elettromagnetico di sistemi RFID in ambito ospedaliero” (in Italian), LA COMUNICAZIONE - Note Recensioni & Notizie, Vol. LX, pp. 119-128, ISSN: 1590-864X, Istituto Superiore delle Comunicazioni e delle Tecnologie dell’Informazione (Ministero dello Sviluppo Economico), Rome, Italy, 2014.

[J-24]   S. Scardapane, D. Wang, M. Panella, and A. Uncini, “Distributed Learning for Random Vector Functional-Link Networks”, Information Sciences, Vol. 301, pp. 271-284, ISSN: 0020-0255, DOI: 10.1016/j.ins.2015.01.007, Elsevier, U.S.A., April 2015.

[J-25]   A. Proietti, M. Panella, F. Leccese, and E. Svezia, “Dust Detection and Analysis in Museum Environment Based on Pattern Recognition”, Measurement, Vol. 66, pp. 62-72, ISSN: 0263-2241, DOI: 10.1016/j.measurement.2015.01.019, Elsevier, U.K., April 2015.

[J-26]   L. Liparulo, A. Proietti, and M. Panella, “Fuzzy Clustering Using the Convex Hull as Geometrical Model”, Advances in Fuzzy Systems, Vol. 2015, Article ID 265135, pp. 1-13, ISSN: 1687-7101, DOI: 10.1155/2015/265135, Hindawi Publishing Corporation, U.S.A., April 2015.

[J-27]   R. Altilio, L. Liparulo, M. Panella, M. Paoloni, and A. Proietti, “Multimedia and Gaming Technologies for Telerehabilitation of Motor Disabilities”, IEEE Technology and Society Magazine, Vol. 34, No. 4, pp. 23-30, ISSN: 0278-0097, DOI: 10.1109/MTS.2015.2494279, IEEE, U.S.A., December 2015.

[J-28]   A. Proietti, L. Liparulo, F. Leccese, and M. Panella, “Shapes classification of dust deposition using fuzzy kernel-based approaches”, Measurement, Vol. 77, pp. 344–350, ISSN: 0263-2241, DOI: 10.1016/j.measurement.2015.09.025, Elsevier, U.K., January 2016.

[J-29]   A. Proietti, L. Liparulo, and M. Panella, “2D hierarchical fuzzy clustering using kernel-based membership functions”, Electronics Letters, Vol. 52, No. 3, pp. 193-195, ISSN: 0013-5194, DOI: 10.1049/el.2015.2602, IET, U.K., February 2016.

[J-30]   E. Baccarelli, N. Cordeschi, A. Mei, M. Panella, M. Shojafar, and J. Stefa, “Energy-Efficient Dynamic Traffic Offloading and Reconfiguration of Networked Data Centers for Big Data Stream Mobile Computing: Review, Challenges, and a Case Study”, IEEE Network, Vol. 30, No. 2, pp. 54-61, ISSN: 0890-8044, DOI: 10.1109/MNET.2016.7437025, IEEE, U.S.A., March-April 2016.

[J-31]   Z. Zhang, L. Liparulo, M. Panella, X. Gu, and Q. Fang, “A Fuzzy Kernel Motion Classifier for Autonomous Stroke Rehabilitation”, IEEE Journal of Biomedical and Health Informatics, Vol. 20, No. 3, pp. 893-901, ISSN: 2168-2194, DOI: 10.1109/JBHI.2015.2430524, IEEE, U.S.A., May 2016.

[J-32]   S. Scardapane, D. Wang, and M. Panella, “A Decentralized Training Algorithm for Echo State Networks in Distributed Big Data Applications”, Neural Networks, Vol. 78, pp. 65-74, ISSN: 0893-6080, DOI: 10.1016/j.neunet.2015.07.006, Elsevier Ltd., U.K., June 2016.

[J-33]   S. Scardapane, R. Fierimonte, P. Di Lorenzo, M. Panella, and A. Uncini, “Distributed Semi-Supervised Support Vector Machines”, Neural Networks, Vol. 80, pp. 43-52, ISSN: 0893-6080, DOI: 10.1016/j.neunet.2016.04.007, Elsevier Ltd., U.K., August 2016.

[J-34]   H. Vahdat-Nejad, M. Panella, and G. Rey, “Introduction to the special section on pervasive computing”, Guest Editor Editorial in Computers & Electrical Engineering, Vol. 55, pp. 24–26, ISSN: 0045-7906, DOI: 10.1016/j.compeleceng.2016.10.010, Elsevier Ltd., U.K., October 2016.

[J-35]   S. Scardapane, M. Panella, D. Comminiello, A. Hussain, and A. Uncini, “Distributed Reservoir Computing with Sparse Readouts”, IEEE Computational Intelligence Magazine, Vol. 11, No. 4, pp. 59-70, ISSN: 1556-603X, DOI: 10.1109/MCI.2016.2601759, IEEE, U.S.A., November 2016.

[J-36]   R. Altilio, M. Paoloni, and M. Panella, “Selection of clinical features for pattern recognition applied to gait analysis”, Medical & Biological Engineering & Computing, Vol. 55, No. 4, pp. 685-695, ISSN: 0140-0118, DOI: 10.1007/s11517-016-1546-1, Springer Berlin Heidelberg, Germany, April 2017.

[J-37]   A. Rosato, R. Altilio, R. Araneo, and M. Panella, “Prediction in Photovoltaic Power by Neural Networks”, invited paper in Energies, Vol. 10, No. 7, Article No. 1003, pp. 1-25, ISSN: 1996-1073, DOI: 10.3390/en10071003, MDPI, Switzerland, July 2017.

[J-38]   L. Liparulo, Z. Zhang, M. Panella, X. Gu, and Q. Fang, “A Novel Fuzzy Approach for Automatic Brunnstrom Stage Classification Using Surface Electromyography”, Medical & Biological Engineering & Computing, Vol. 55, No. 8, pp. 1367-1378, ISSN: 0140-0118, DOI: 10.1007/s11517-016-1597-3, Springer Berlin Heidelberg, Germany, August 2017.

[J-39]   R. Fierimonte, S. Scardapane, A. Uncini, and M. Panella, “Fully Decentralized Semi-supervised Learning via Privacy-preserving Matrix Completion”, IEEE Transactions on Neural Networks and Learning Systems, Vol. 28, No. 11, pp. 2699-2711, ISSN: 2162-237X, DOI: 10.1109/TNNLS.2016.2597444, IEEE, U.S.A., November 2017.

[J-40]   M. Panella and R. Altilio, “A Smartphone-Based Application Using Machine Learning for Gesture Recognition: Using Feature Extraction and Template Matching via Hu Image Moments to Recognize Gestures”, IEEE Consumer Electronics Magazine, Vol. 8, No. 1, pp. 25-29, ISSN: 2162-2248, DOI: 10.1109/MCE.2018.2868109, IEEE, U.S.A., January 2019.

[J-41]   A. Rosato, M. Panella, and R. Araneo, “A Distributed Algorithm for the Cooperative Prediction of Power Production in PV Plants”, IEEE Transactions on Energy Conversion, Vol. 34, No. 1, pp. 497-508, ISSN: 0885-8969, DOI: 10.1109/TEC.2018.2873009, IEEE, U.S.A., March 2019.

[J-42]   A. Micarelli, A. Viziano, M. Panella, E. Micarelli, and M. Alessandrini, “Power spectra prognostic aspects of impulsive eye movement traces in superior vestibular neuritis”, Medical & Biological Engineering & Computing, Vol. 57, No. 8, pp. 1617-1627, ISSN: 0140-0118, DOI: 10.1007/s11517-019-01982-3, Springer Berlin Heidelberg, Germany, August 2019.

[J-43]   R. Altilio, P. Di Lorenzo, and M. Panella, “Distributed data clustering over networks”, Pattern Recognition, Vol. 93, pp. 603-620, ISSN: 0031-3203, DOI: 10.1016/j.patcog.2019.04.021, Elsevier Ltd., U.K., September 2019.

[J-44] A. Stolfi, F. Angeletti, P. Gasbarri, and M. Panella, “A Deep Learning Strategy for On‑Orbit Servicing Via Space Robotic Manipulator”, Aerotecnica Missili & Spazio, Vol. 98, pp. 273-282, ISSN: 0365-7442, DOI: 10.1007/s42496-019-00028-z, Springer Nature, Switzerland, November 2019.

[J-45] A. Rosato, M. Panella, R. Araneo, and A. Andreotti, “A Neural Network Based Prediction System of Distributed Generation for the Management of Microgrids”, IEEE Transactions on Industry Applications, Vol. 55, No. 6, pp. 7092-7102, ISSN: 0093-9994, DOI: 10.1109/TIA.2019.2916758, IEEE, U.S.A., November-December 2019.

[J-46] F. Succetti, A. Rosato, R. Araneo, and M. Panella, “Deep Neural Networks for Multivariate Prediction of Photovoltaic Power Time Series”, IEEE Access, Vol. 8, pp. 211490-211505, ISSN: 2169-3536, DOI: 10.1109/ACCESS.2020.3039733, IEEE, U.S.A., December 2020.

[J-47] F. De Caro, A. Andreotti, R. Araneo, M. Panella, A. Rosato, A. Vaccaro, and D. Villacci, “A Review of the Enabling Methodologies for Knowledge Discovery from Smart Grids Data”, articolo selezionato in Energies, Vol. 13, No. 24, Article No. 6579, pp. 1-25, ISSN: 1996-1073, DOI: 10.3390/en13246579, MDPI, Switzerland, December 2020.

[J-48] R. Altilio, A. Rossetti, Q. Fang, X. Gu, and M. Panella, “A comparison of machine learning classifiers for smartphone-based gait analysis”, Medical & Biological Engineering & Computing, Vol. 59, No. 3, pp. 535-546, ISSN: 0140-0118, DOI: 10.1007/s11517-020-02295-6, Springer Nature, Switzerland, March 2021.

[J-49] G.C. Cardarilli, L. Di Nunzio, R. Fazzolari, M. Panella, M. Re, A. Rosato, and S. Spanò, “A Parallel Hardware Implementation for 2-D Hierarchical Clustering Based on Fuzzy Logic”, IEEE Transactions on Circuits and Systems II: Express Briefs, Vol. 68, No. 4, pp. 1428-1432, ISSN: 1549-7747, DOI: 10.1109/TCSII.2020.3032660, IEEE, U.S.A., April 2021.

[J-50] A. Rosato, M. Panella, A. Andreotti, O.A. Mohammed, and R. Araneo, “Two-stage dynamic management in energy communities using a decision system based on elastic net regularization”, Applied Energy, Vol. 291, Article No. 116852, pp. 1-12, ISSN: 0306-2619, DOI: 10.1016/j.apenergy.2021.116852, Elsevier Ltd., U.K., June 2021.

[J-51] A. Rosato, R. Araneo, A. Andreotti, F. Succetti, and M. Panella, “2-D Convolutional Deep Neural Network for the Multivariate Prediction of Photovoltaic Time Series”, Energies, Vol. 14, No. 9, Article No. 2392, pp. 1-18, ISSN: 1996-1073, DOI: 10.3390/en14092392, MDPI, Switzerland, April 2021.

[J-52] A. Rosato, R. Altilio, and M. Panella, “A decentralized algorithm for distributed ensemble clustering”, Information Sciences, Vol. 578, pp. 417-434, ISSN: 0020-0255, DOI: 10.1016/j.ins.2021.07.028, Elsevier Inc., U.S.A., November 2021.

[J-53] P. Iannelli, F. Angeletti, P. Gasbarri, M. Panella, and A. Rosato, “Deep learning-based Structural Health Monitoring for damage detection on a large space antenna”, Acta Astronautica, Vol. 193, pp. 635-643, ISSN 0094-5765, DOI: 10.1016/j.actaastro.2021.08.003, Elsevier Ltd., U.K., April 2022.

[J-54] A. Ceschini, A. Rosato, and M. Panella, “Design of an LSTM Cell on a Quantum Hardware”, IEEE Transactions on Circuits and Systems II: Express Briefs, Vol. 69, No. 3, pp. 1822-1826, ISSN: 1549-7747, DOI: 10.1109/TCSII.2021.3126204, IEEE, U.S.A., March 2022.

[J-55] F. Succetti, A. Rosato, F. Di Luzio, A. Ceschini, and M. Panella, “A Fast Deep Learning Technique for Wi-Fi-Based Human Activity Recognition”, invited paper in Progress In Electromagnetics Research, Vol. 174, pp. 127-141, ISSN: 1070-4698, DOI: 10.2528/PIER22042605, The Electromagnetics Academy, U.S.A., July 2022.

[J-56] T. Catena, V. Eramo, M. Panella, and A. Rosato, “Distributed LSTM-based cloud resource allocation in Network Function Virtualization Architectures”, Computer Networks, Vol. 213, Article No. 109111, pp. 1-12, ISSN: 1389-1286, DOI: 10.1016/j.comnet.2022.109111, Elsevier B.V., The Netherlands, August 2022.

[J-57] F. Angeletti, P. Iannelli, P. Gasbarri, M. Panella, and A. Rosato, “A Study on Structural Health Monitoring of a Large Space Antenna via Distributed Sensors and Deep Learning”, Sensors, Vol. 23, No. 1, Article No. 368., pp. 1-20, ISSN: 1424-8220, DOI: 10.3390/s23010368, MDPI, Switzerland, January 2023.

[J-58] F. Succetti, A. Rosato, R. Araneo, G. Di Lorenzo, and M. Panella, “Challenges and Perspectives of Smart Grid Systems in Islands: A Real Case Study”, Energies, Vol. 16, No. 2, Article No. 583, pp. 1-37, ISSN: 1996-1073, DOI: 10.3390/en16020583, MDPI, Switzerland, January 2023.

[J-59] F. Di Luzio, A. Rosato, and M. Panella, “A randomized deep neural network for emotion recognition with landmarks detection”, Biomedical Signal Processing and Control, Vol. 81, Article No. 104418, pp. 1-9, ISSN: 1746-8094, DOI: 10.1016/j.bspc.2022.104418, Elsevier Ltd., U.K., March 2023.

[J-60] F. Angeletti, P. Gasbarri, M. Panella, and A. Rosato, “Multi-Damage Detection in Composite Space Structures via Deep Learning”, Sensors, Vol. 23, No. 17, Article No. 7515, pp. 1-22, ISSN: 1424-8220, DOI: 10.3390/s23177515, MDPI, Switzerland, August 2023.

[J-61] E. Stracqualursi, A. Rosato, G. Di Lorenzo, M. Panella, and R. Araneo, “Systematic review of energy theft practices and autonomous detection through artificial intelligence methods”, Renewable and Sustainable Energy Reviews, Vol. 184, Article No. 113544, pp. 1-19, ISSN: 1364-0321, DOI: 10.1016/j.rser.2023.113544, Elsevier Ltd., U.K., September 2023.

[J-62] F. Succetti, A. Rosato, and M. Panella, “An Adaptive Embedding Procedure for Time Series Forecasting with Deep Neural Networks”, Neural Networks, Vol. 167, pp. 715-729, ISSN: 0893-6080, DOI: 10.1016/j.neunet.2023.08.051, Elsevier Ltd., U.K., October 2023.

[J-63] M. Incudini, M. Grossi, A. Ceschini, A. Mandarino, M. Panella, S. Vallecorsa, and D. Windridge, “Resource saving via ensemble techniques for quantum neural networks”, Quantum Machine Intelligence, Vol. 5, No. 2, Article No. 39, pp. 1-24, ISSN: 2524-4906, DOI: 10.1007/s42484-023-00126-z, Springer Nature, Germany, December 2023.

[J-64] A. Ceschini, A. Rosato, and M. Panella, “Modular quantum circuits for secure communication”, IET Quantum Communication, Vol. 4, No. 4, pp. 208-217, ISSN: 2632-8925, DOI: 10.1049/qtc2.12065, John Wiley & Sons Ltd (on behalf of The Institution of Engineering and Technology – IET), U.K., December 2023.

[J-65] F. Scala, A. Ceschini, M. Panella, and D. Gerace, “A General Approach to Dropout in Quantum Neural Networks”, Advanced Quantum Technologies, ISSN: 2511-9044, DOI: 10.1002/qute.202300220, Wiley-VCH, Germany, 2023 (early access).

[J-66] A. Verdone, S. Scardapane, and M. Panella, “Explainable Spatio-Temporal Graph Neural Networks for multi-site photovoltaic energy production”, Applied Energy, Vol. 353 (Part B), Article No. 122151, pp. 1-13, ISSN: 0306-2619, DOI: 10.1016/j.apenergy.2023.122151, Elsevier Ltd., U.K., January 2024.

[J-67] F. Colonnese, F. Di Luzio, A. Rosato, and M. Panella, “Bimodal Feature Analysis with Deep Learning for Autism Spectrum Disorder Detection”, invited paper in International Journal of Neural Systems, Vol. 34, No. 2, Article No. 2450005, pp. 1-16, ISSN: 0129-0657, DOI: 10.1142/S0129065724500059, World Scientific Publishing, Singapore, February 2024.

[J-68] D. Kleyko, A. Rosato, E. Paxon Frady, M. Panella, and F.T. Sommer, “Perceptron Theory Can Predict the Accuracy of Neural Networks”, IEEE Transactions on Neural Networks and Learning Systems, Vol. 35, No. 7, pp. 9885-9899, ISSN: 2162-237X, DOI: 10.1109/TNNLS.2023.3237381, IEEE, U.S.A., July 2024.

[J-69] A. Ceschini, A. Rosato, and M. Panella, “A Variational Approach to Quantum Gated Recurrent Units”, Journal of Physics Communications, Vol. 8, No. 8, Article No. 085004, pp. 1-16, ISSN: 2399-6528, DOI: 10.1088/2399-6528/ad6db7, Institute of Physics Publishing, U.K., August 2024.

[J-70] F. De Falco, A. Ceschini, A. Sebastianelli, B. Le Saux, and M. Panella, “Quantum Latent Diffusion Models”, Quantum Machine Intelligence, Vol. 6, No. 2, Article No. 85, pp. 1-20, ISSN: 2524-4906, DOI: 10.1007/s42484-024-00224-6, Springer Nature, Switzerland, December 2024.

[J-71] A. Sebastianelli, F. Serva, A. Ceschini, Q. Paletta, M. Panella, and B. Le Saux, “Machine learning forecast of surface solar irradiance from meteo satellite data”, Remote Sensing of Environment, Vol. 315, Article No. 114431, pp. 1-13, ISSN: 0034-4257, DOI: 10.1016/j.rse.2024.114431, Elsevier Inc., U.S.A., December 2024.

[J-72] F. Colonnese, F. Di Luzio, A. Rosato, and M. Panella, “Enhancing Autism Detection Through Gaze Analysis Using Eye Tracking Sensors and Data Attribution with Distillation in Deep Neural Networks”, invited paper in Sensors, Vol. 24, No. 23, Article No. 7792, pp. 1-16, ISSN: 1424-8220, DOI: 10.3390/s24237792, MDPI, Switzerland, December 2024.

[J-73] F. De Falco, A. Ceschini, A. Sebastianelli, B. Le Saux, and M. Panella, “Quantum Hybrid Diffusion Models for Image Synthesis”, KI - Künstliche Intelligenz (German Journal of Artificial Intelligence), Vol. 38, No. 4, pp. 311-326, ISSN: 0933-1875, DOI: 10.1007/s13218-024-00858-5, Springer Nature, Germany, December 2024.

[J-74] S. Perilli, M. Di Pietro, E. Mantini, M. Regazzetti, P. Kiper, F. Galliani, M. Panella, and D. Mantini, “Development of a Wearable Electromyographic Sensor with Aerosol Jet Printing Technology”, Bioengineering, Vol. 11, No. 12, Article No. 1283, pp. 1-13, ISSN: 2306-5354, DOI: 10.3390/bioengineering11121283, MDPI, Switzerland, December 2024.

[J-75] F. Succetti, A. Rosato, and M. Panella, “Multi-label Classification with Imbalanced Classes by Fuzzy Deep Neural Networks”, invited paper in Integrated Computer-Aided Engineering, Vol. 32, No. 1, pp. 23-36, ISSN: 1069-2509, DOI: 10.3233/ICA-240736, IOS Press, The Netherlands, February  2025.

[J-76] F. Di Luzio, A. Rosato, and M. Panella, “An explainable fast deep neural network for emotion recognition”, Biomedical Signal Processing and Control, Volume 100, Part B, Article No. 107177, pp. 1-10, ISSN: 1746-8094, DOI: 10.1016/j.bspc.2024.107177, Elsevier Ltd., U.K., February 2025.

[J-77] A. Ceschini, A. Carbone, A. Sebastianelli, M. Panella, and B. Le Saux, “On Hybrid Quanvolutional Neural Networks Optimization”, Quantum Machine Intelligence, Vol. 7, No. 1, Article No. 18, pp. 1-17, ISSN: 2524-4906, DOI: 10.1007/s42484-025-00241-z, Springer Nature, Switzerland, June 2025.

[J-78] S. Piperno, A. Ceschini, S.Y. Chang, M. Grossi, S. Vallecorsa, and M. Panella, “A Study on Quantum Graph Neural Networks Applied to Molecular Physics”, Physica Scripta, Vol. 100, No. 6, Article No. 065126, pp. 1-18, ISSN: 0031-8949, DOI: 10.1088/1402-4896/add8e9, IOP Publishing Ltd., U.K., June 2025.

[J-79] A. Verdone, M. Panella, E. De Santis, and A. Rizzi, “A review of solar and wind energy forecasting: From single-site to multi-site paradigm”, Applied Energy, Vol. 392, Article No. 126016, pp. 1-19, ISSN: 0306-2619, DOI: 10.1016/j.apenergy.2025.126016, Elsevier Ltd., U.K., August 2025.

[J-80] C. Mantuano, O. Omoyele, M. Hoffmann, J.M. Weinand, M. Panella, and D. Stolten “Data imputation methods for intermittent renewable energy sources: Implications for energy system modeling”, Energy Conversion and Management, Vol. 339, Article No. 119857, pp. 1-22, ISSN: 0196-8904, DOI: 10.1016/j.enconman.2025.119857, Elsevier Ltd., U.K., September 2025.

International Conference Proceedings

[C-1]   F.M. Frattale Mascioli, A. Rizzi, M. Panella, and G. Martinelli, “Clustering with Unconstrained Hyperboxes”, Proc. of IEEE International Fuzzy Systems Conference (FUZZ-IEEE ’99), Vol. 2, pp. 1075-1080, ISBN: 0780354060, ISSN: 1544-5615, DOI: 10.1109/FUZZY.1999.793103, IEEE, Seoul, Corea, 22-25 August 1999.

[C-2]   M. Panella, F.M. Frattale Mascioli, A. Rizzi, and G. Martinelli, “Optimisation of Bayesian Classifiers by Using a Splitting Hierarchical EM Algorithm”, Proc. of Neural Computation (NC’2000), pp. 1-7, ISBN: 3-906454-21-5, ICSC Academic Press, Berlin, Germany, 23-26 May 2000.

[C-3]   G. Costantini, P. Antici, M. Panella, and F.M. Frattale Mascioli, “Nonexclusive classification of musical sources using pattern recognition”, Proc. of Engineering of Intelligent Systems (EIS’2000), pp. 1-5, ISBN: 3-906454-21-5, ICSC Academic Press, Paisley, Scotland, U.K., 27-30 June 2000.

[C-4]   A. Rizzi, M. Panella, F.M. Frattale Mascioli, and G. Martinelli, “A Recursive Algorithm for Fuzzy Min-Max Networks”, Proc. of IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN 2000), Vol. 6, pp. 541-546, ISBN: 0-7695-0619-4, ISSN: 2161-4407, DOI: 10.1109/IJCNN.2000.859451, IEEE, Como, Italy, 24-27 July 2000.

[C-5]   G. Costantini, P. Antici, M. Panella, and F.M. Frattale Mascioli, “Nonexclusive classification and recognition of traditional musical instruments”, Proc. of XIII Colloquium on Musical Informatics (CIM 2000), pp. 119-122, Istituto GRAMMA, L’Aquila, Italy, 2-5 September 2000.

[C-6]   F.M. Frattale Mascioli, M. Panella, A. Rizzi, and G. Martinelli, “Scale-Based Clustering with Latent Variables”, Proc. of European Signal Processing Conference (EUSIPCO 2000), in Signal Processing X: Theories and Applications (M. Gabbouj and P. Kuosmanen Eds.), Vol. II, pp. 741-744, ISBN: 9521504439, EURASIP and Tampere University of Technology, Tampere, Finlandia, 4-8 September 2000 (printed in European Signal Processing Conference, Vol. 2015, Article no. 7075635, ISSN: 2219-5491, 31 March 2015).

[C-7]   M. Panella, A. Rizzi, F.M. Frattale Mascioli, and G. Martinelli, “A Constructive EM Approach to Density Estimation for Learning”, Proc. of International Joint Conference on Neural Networks (IJCNN ‘01), Vol. 4, pp. 2608-2613, ISBN: 0-7803-7044-9, ISSN: 2161-4407, DOI: 10.1109/IJCNN.2001.938781, IEEE, Washington D.C., U.S.A., 14-19 July 2001.

[C-8]   M. Panella, A. Rizzi, F.M. Frattale Mascioli, and G. Martinelli, “ANFIS Synthesis by Hyperplane Clustering”, Proc. of Joint IFSA World Congress and NAFIPS International Conference (IFSA/NAFIPS 2001), Vol. 1, pp. 340-345, ISBN: 0-7803-7078-3, DOI: 10.1109/NAFIPS.2001.944275, IEEE, Vancouver, Canada, 25-28 July 2001.

[C-9]   A. Rizzi, M. Panella, F.M. Frattale Mascioli, and G. Martinelli, “Automatic Training of Generalized Min-Max Classifiers”, Proc. of Joint IFSA World Congress and NAFIPS International Conference (IFSA/NAFIPS 2001), Vol. 5, pp. 3070-3075, ISBN: 0-7803-7078-3, DOI: 10.1109/NAFIPS.2001.943718, IEEE, Vancouver, Canada, 25-28 July 2001.

[C-10]   M. Panella, A. Rizzi, F.M. Frattale Mascioli, and G. Martinelli, “Improved Time Series Forecasting by a Twofold Neural Predictor”, Proc. of International Conference on Engineering Applications of Neural Networks (EANN 2001), pp. 196-203, ISBN: 88-88342-00-1, Ed. CUSL, Cagliari, Italy, 16-18 July 2001.

[C-11]   M. Panella, A. Rizzi, F.M. Frattale Mascioli, and G. Martinelli, “Constructive MoG Neural Networks for Pollution Data Forecasting”, Proc. of International Joint Conference on Neural Networks (IJCNN ‘02), Vol. 1, pp. 417-422, ISBN: 0-7803-7278-6, ISSN: 2161-4407, DOI: 10.1109/IJCNN.2002.1005508, IEEE, Honoloulu, Hawaii, U.S.A., 12-17 May 2002.

[C-12]   A. Rizzi, M. Panella, F.M. Frattale Mascioli, and G. Martinelli, “Automatic Feature Selection for Adaptive Resolution Classifiers”, Proc. of IEEE International Conference on Fuzzy Systems (FUZZ-IEEE ‘02), Vol. 1, pp. 384-389, ISBN: 0-7803-7280-8, 1544-5615, DOI: 10.1109/FUZZ.2002.1005021, IEEE, Honoloulu, Hawaii, U.S.A., 12-17 May 2002.

[C-13]   M. Panella, F.M. Frattale Mascioli, A. Rizzi, and G. Martinelli, “Improving accuracy of electric load short-term forecasting by using MoG neural networks”, Applicazioni di Reti Neurali nell’Ingegneria Elettrica ed Elettromagnetica (Giornata di Studio), in Atti della “Fondazione Giorgio Ronchi”, Anno LVII, No. 4, pp. 689-692, ISSN: 0391 2051, Fondazione “GIORGIO RONCHI”, Florence, Italy, 4-5 April 2002.

[C-14]   M. Panella, A. Rizzi, F.M. Frattale Mascioli, and G. Martinelli, “A Neuro-fuzzy Approach to Partial Discharge Pattern Recognition of XLPE Insulated MV Cables”, Proc. of International Conference on Engineering Applications of Neural Networks (EANN’03), pp. 184-191, ISBN: 84-930984-1-8, Ed. Dpt. ISA, Malaga, Spain, 8-10 September 2003.

[C-15]   F.M. Frattale Mascioli, M. Panella, and A. Rizzi, “A Neural Prediction of Multi-Sensor Systems”, Proc. of World Automation Congress (WAC 2004), Vol. 17, pp. 1-6, ISBN: 1-889335-21-5, TSI Press, Seville, Spain, 28 June-1 July 2004.

[C-16]   A. Rizzi, M. Panella, M. Paschero, and F.M. Frattale Mascioli, “Estimation of Bone Mineral Density Data Using MoG Neural Networks”, Proc. of IEEE International Joint Conference on Neural Networks (IJCNN 2004), Vol. 4, pp. 3241-3246, ISBN: 0-7803-8359-1, ISSN: 2161-4407, DOI: 10.1109/IJCNN.2004.1381198, IEEE, Budapest, Hungary, 25-29 July 2004.

[C-17]   M. Panella, M. Paschero, and F.M. Frattale Mascioli, “A Modular RC-Active Network for Vibration Damping in Piezo-Electro-Mechanical Beams”, Proc. of IEEE International Symposium on Circuits and Systems (ISCAS 2005), Vol. 6, pp. 5393-5396, ISBN: 0-7803-8834-8, ISSN: 0271-4302, DOI: 10.1109/ISCAS.2005.1465855, IEEE, Kobe, Japan, 23-26 May 2005.

[C-18]   M. Panella, M. Paschero, and F.M. Frattale Mascioli, “Symbolic Analysis and Optimization of Piezo-Electromechanical Systems”, Proc. of IEEE International Symposium on Circuits and Systems (ISCAS 2006), pp. 633-636, ISBN: 0-7803-9390-2, ISSN: 0271-4302, DOI: 10.1109/ISCAS.2006.1692665, IEEE, Isola di Kos, Greece, 21-24 May 2006.

[C-19]   M. Panella and A. Rizzi, “Baseband Filter Banks for Neural Prediction”, Proc. of International Conference on Computational Intelligence for Modelling, Control and Automation & International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA 2006/IAWTIC 2006), pp. 1-6, ISBN: 0-7695-2731-0, DOI: 10.1109/CIMCA.2006.57, IEEE, Sydney, Australia, 28 November-01 December 2006.

[C-20]   A. Rizzi, M. Buccino, M. Panella, and A. Uncini, “Optimal Short-Time Features for Music/Speech Classification of Compressed Audio Data”, Proc. of International Conference on Computational Intelligence for Modelling, Control and Automation & International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA 2006/IAWTIC 2006), pp. 1-6, ISBN: 0-7695-2731-0, DOI: 10.1109/CIMCA.2006.160, IEEE Computer Society, Sydney, Australia, 28 November-01 December 2006.

[C-21]   R. Parisi, A. Cirillo, M. Panella, and A. Uncini, “Source Localization in Reverberant Environments by Consistent Peak Selection”, Proc. of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2007), Vol. 1, pp. I-37-I-40, ISBN: 1-4244-0728-1, ISSN: 1520-6149, DOI: 10.1109/ICASSP.2007.366610, IEEE, Honoloulu, Hawaii, U.S.A., 15-20 April 2007.

[C-22]   A. Rizzi, N.M. Buccino, M. Panella, and A. Uncini, “Genre Classification of Compressed Audio Data”, Proc. of IEEE Workshop on Multimedia Signal Processing (MMSP 2008), pp. 654-659, ISBN: 978-1-4244-2294-4, DOI: 10.1109/MMSP.2008.4665157, IEEE, Cairns, Australia, 8-10 October 2008.

[C-23]   M. Panella, F. Barcellona, and G. Orlandi, “Prediction of Biological Time Series by Genetic Embedding”, Proc. of International Symposium on Bioelectronics and Bioinformatics (ISBB2009), pp. 41-44, ISBN: 978-0-9807314-0-8, Qiang Fang and Irena Cosic Eds., Melbourne, Australia, 09-11 December 2009.

[C-24]   M. Panella and F.M. Frattale Mascioli, “A Tuning Procedure for the Electric Networks of PEM Systems”, Proc. of IEEE International Symposium on Circuits and Systems (ISCAS 2010), pp. 3272- 3275, ISBN: 978-1-4244-5308-5, ISSN: 0271-4302, DOI: 10.1109/ISCAS.2010.5537913, IEEE, Paris, France, 30 May-02 June 2010.

[C-25]   M. Panella, F. Barcellona, and V. Santucci, “Modeling the dynamics of energy commodity prices using neural networks”, 48th Euro Working Group on Financial Modelling (48th EWGFM 2011), conference abstract, pp. 1-2, Euro Working Group on Financial Modelling, Beirut, Lebanon, 5-7 May 2011.

[C-26]   M. Panella, F. Barcellona, V. Santucci, and R. D’Ecclesia, “Neural Networks to Model Energy Commodity Price Dynamics”, 30th USAEE/IAEE North American Conference (USAEE 2011), pp. 1-4, conference abstract, USAEE/IAEE, Washington D.C., U.S.A., 9-12 October 2011.

[C-27]   M. Panella, F. Barcellona, and R.L. D’Ecclesia, “Subband Prediction of Energy Commodity Prices”, Proc. of the IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2012), invited at Special Session, pp. 495-499, ISBN: 978-1-4673-0971-4, ISSN: 1948-3244, DOI: 10.1109/SPAWC.2012.6292957, IEEE, Çeşme, Turkey, 17-20 June 2012.

[C-28]   M. Panella, F. Barcellona, and R.L. D’Ecclesia, “Modeling Energy Markets Using Neural Networks and Spectral Analysis”, 12th IAEE European Energy Conference, pp. 1-2, conference abstract, AIEE/IAEE, Venice, Italy, 9-12 September 2012.

[C-29]   L. Liparulo, A. Proietti, and M. Panella, “Fuzzy membership functions based on point-to-polygon distance evaluation”, Proc. of IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2013), pp. 1-8, ISBN: 978-147990022-0, ISSN: 1544-5615, DOI: 10.1109/FUZZ-IEEE.2013.6622449, IEEE, Hyderabad, India, 7-10 July 2013.

[C-30]   M. Panella, L. Liparulo, F. Barcellona, and R. D’Ecclesia, “A study on crude oil prices modeled by neurofuzzy networks”, Proc. of IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2013), pp. 1-7, ISBN: 978-147990022-0, ISSN: 1544-5615, DOI: 10.1109/FUZZ-IEEE.2013.6622496, IEEE, Hyderabad, India, 7-10 July 2013.

[C-31] M. Panella and A. Proietti, “A Data Driven Circuit Model for Rechargeable Batteries”, Proc. of IEEE International Symposium on Circuits and Systems (ISCAS 2014), pp. 626-629, ISBN: 978-1-4799-3432-4, ISSN: 0271-4302, DOI: 10.1109/ISCAS.2014.6865213, IEEE, Melbourne, Australia, 1-5 June 2014.

[C-32]   M. Panella, L. Liparulo, and A. Proietti, “A Higher-Order Fuzzy Neural Network for Modeling Financial Time Series”, Proc. of International Joint Conference on Neural Networks (IJCNN 2014), pp. 3066-3073, ISBN: 978-1-4799-1484-5, ISSN: 2161-4393, DOI: 10.1109/IJCNN.2014.6889574, IEEE, Beijing, China, 6-11 July 2014.

[C-33]   S. Scardapane, R. Fierimonte, D. Wang, M. Panella, and A. Uncini, “Distributed Music Classification Using Random Vector Functional-Link Nets”, Proc. of International Joint Conference on Neural Networks (IJCNN 2015), pp. 272-279, ISBN: 978-1-4799-1959-8, ISSN: 2161-4407, DOI: 10.1109/IJCNN.2015.7280333, IEEE, Killarney, Republic of Ireland, 12-17 July 2015.

[C-34]   T. Colombo, I. Koprinska, and M. Panella, “Maximum Length Weighted Nearest Neighbor Approach for Electricity Load Forecasting”, Proc. of International Joint Conference on Neural Networks (IJCNN 2015), pp. 3751-3758, ISBN: 978-1-4799-1959-8, ISSN: 2161-4407, DOI: 10.1109/IJCNN.2015.7280809, IEEE, Killarney, Republic of Ireland, 12-17 July 2015.

[C-35]   L. Liparulo, A. Proietti, and M. Panella, “Improved Online Fuzzy Clustering Based on Unconstrained Kernels”, Proc. of IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2015), pp. 1-8, ISBN: 978-1-4673-7428-6, ISSN: 1544-5615, DOI: 10.1109/FUZZ-IEEE.2015.7338065, IEEE, Istanbul, Turkey, 2-5 August 2015.

[C-36]   S. Scardapane, M. Panella, D. Comminiello, and A. Uncini, “Learning from Distributed Data Sources Using Random Vector Functional-Link Networks”, Proc. of INNS Conference on Big Data (INNS-Big Data 2015) in Procedia Computer Science, Vol. 53, pp. 468–477, ISSN: 1877-0509, DOI: 10.1016/j.procs.2015.07.324, Elsevier B.V., San Francisco, U.S.A., 8-10 August 2015.

[C-37]   A. Proietti, M. Panella, E. D. Di Claudio, G. Jacovitti, and G. Orlandi, “Classification of Dust Elements by Spatial Geometric Features”, Proc. of the International Conference on Pattern Recognition Applications and Methods (ICPRAM 2016), pp. 247-254, ISBN: 978-989-758-173-1, SCITEPRESS, Rome, Italy, 24-26 February 2016.

[C-38]   A. Rosato, R. Altilio, R. Araneo, and M. Panella, “Embedding of Time Series for the Prediction in Photovoltaic Power Plants”, Proc. of IEEE International Conference on Environment and Electrical Engineering (IEEE EEEIC 2016), pp. 1-4, ISBN: 978-1-5090-2320-2, 978-1-5090-2319-6, DOI: 10.1109/EEEIC.2016.7555872, IEEE, Florence, Italy, 7-10 June 2016.

[C-39]   S. Scardapane, R. Altilio, M. Panella, and A. Uncini, “Distributed Spectral Clustering based on Euclidean Distance Matrix Completion”, Proc. of International Joint Conference on Neural Networks (IJCNN 2016), pp. 3093-3100, ISBN: 978-1-5090-0620-5, ISSN: 2161-4407, DOI: 10.1109/IJCNN.2016.7727593, IEEE, Vancouver, Canada, 24-29 July 2016.

[C-40]   R. Fierimonte, M. Barbato, A. Rosato, and M. Panella, “Distributed Learning of Random Weights Fuzzy Neural Networks”, Proc. of IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2016), pp. 2287-2294, ISBN: 978-1-5090-0626-7, ISSN: 1544-5615, DOI: 10.1109/FUZZ-IEEE.2016.7737978, IEEE, Vancouver, Canada, 24-29 July 2016.

[C-41]   R. Altilio, L. Liparulo, A. Proietti, M. Paoloni, and M. Panella, “A Genetic Algorithm for Feature Selection in Gait Analysis”, Proc. of IEEE Congress on Evolutionary Computation (IEEE CEC 2016), pp. 4584-4591, ISBN: 978-1-5090-0623-6, DOI: 10.1109/CEC.2016.7744374, IEEE, Vancouver, Canada, 24-29 July 2016.

[C-42]   A. Rosato, R. Altilio, R. Araneo, and M. Panella, “Takagi-Sugeno Fuzzy Systems Applied to Voltage Prediction of Photovoltaic Plants”, Proc. of IEEE International Conference on Environment and Electrical Engineering and IEEE Industrial and Commercial Power Systems Europe (IEEE EEEIC / I&CPS Europe 2017), pp. 1-6, ISBN: 9781538639177, DOI: 10.1109/EEEIC.2017.7977784, IEEE, Milan, Italy, 6-9 June 2017.

[C-43]   R. Fierimonte, R. Altilio, and M. Panella, “Distributed On-line Learning for Random-Weight Fuzzy Neural Networks”, Proc. of IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2017), pp. 1-6, ISBN: 978-1-5090-6034-4, ISSN: 1544-5615, DOI: 10.1109/FUZZ-IEEE.2017.8015727, IEEE, Naples, Italy, 9-12 July 2017.

[C-44]   R. Altilio, A. Rosato, and M. Panella, “A New Learning Approach for Takagi-Sugeno Fuzzy Systems Applied to Time Series Prediction”, Proc. of IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2017), pp. 1-6, ISBN: 978-1-5090-6034-4, ISSN: 1544-5615, DOI: 10.1109/FUZZ-IEEE.2017.8015723, IEEE, Naples, Italy, 9-12 July 2017.

[C-45]   A. Rosato, R. Altilio, and M. Panella, “Finite Precision Implementation of Random Vector Functional-Link Networks”, Proc. of International Conference on Digital Signal Processing (DSP 2017), pp. 1-5, ISBN: 978-1-5386-1895-0, ISSN: 2165-3577, DOI: 10.1109/ICDSP.2017.8096056, IEEE, London, U.K., 23-25 August 2017.

[C-46]   R. Altilio, A. Rosato, and M. Panella, “A Nonuniform Quantizer for Hardware Implementation of Neural Networks”, Proc. of European Conference on Circuit Theory and Design (ECCTD 2017), pp. 1-4, ISBN: 978-1-5386-3974-0, ISSN: 2474-9672, DOI: 10.1109/ECCTD.2017.8093264, IEEE, Catania, Italy, 4-6 September 2017.

[C-47]   H.A. Nascimento Silva, G. Laneve, A. Rosato, and M. Panella, “Retrieving Chlorophyll-a Levels, Transparency and TSS Concentration from Multispectral Satellite Data by Using Artificial Neural Networks”, Proc. of Progress in ElectRomegnetics Research Symposium - Fall (PIERS - FALL 2017), pp. 2876-2883, ISBN: 978-1-5386-1211-8, ISSN: 1559-9450, DOI: 10.1109/PIERS-FALL.2017.8293624, IEEE, Singapore, 19-22 November 2017.

[C-48]   A. Rosato, R. Altilio, and M. Panella, “On-line Learning of RVFL Neural Networks on Finite Precision Hardware”, Proc. of IEEE International Symposium on Circuits and Systems (ISCAS 2018), pp. 1-5, ISBN: 978-1-5386-4881-0, ISSN: 2379-447X, DOI: 10.1109/ISCAS.2018.8351399, IEEE, Florence, Italy, 27-30 May 2018.

[C-49]   A. Rosato, R. Altilio, R. Araneo, and M. Panella, “A Smart Grid in Ponza Island: Battery Energy Storage Management by Echo State Neural Network”, Proc. of IEEE International Conference on Environment and Electrical Engineering and IEEE Industrial and Commercial Power Systems Europe (IEEE EEEIC / I&CPS Europe 2018), pp. 1-4, ISBN: 978-1-5386-5186-5, DOI: 10.1109/EEEIC.2018.8493820, IEEE, Palermo, Italy, 12-15 June 2018.

[C-50]   A. Rosato, R. Altilio, R. Araneo, and M. Panella, “Neural Network Approaches to Electricity Price Forecasting in Day-Ahead Markets”, Proc. of IEEE International Conference on Environment and Electrical Engineering and IEEE Industrial and Commercial Power Systems Europe (IEEE EEEIC / I&CPS Europe 2018), pp. 1-5, ISBN: 978-1-5386-5186-5, DOI: 10.1109/EEEIC.2018.8493837, IEEE, Palermo, Italy, 12-15 June 2018.

[C-51]   H.A. Nascimento Silva, A. Rosato, R. Altilio, and M. Panella, “Water Quality Prediction Based on Wavelet Neural Networks and Remote Sensing”, Proc. of International Joint Conference on Neural Networks (IJCNN 2018), pp. 1-6, ISBN: 978-1-5090-6014-6, ISSN: 2161-4407, DOI: 10.1109/IJCNN.2018.8489662, IEEE, Rio de Janeiro, Brasil, 8-13 July 2018.

[C-52]   R. Altilio, A. Rosato, and M. Panella, “A Sparse Bayesian Model for Random Weight Fuzzy Neural Networks”, Proc. of IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2018), pp. 1-7, ISBN: 978-1-5090-6020-7, ISSN: 1544-5615, DOI: 10.1109/FUZZ-IEEE.2018.8491645, IEEE, Rio de Janeiro, Brasil, 8-13 July 2018.

[C-53]   H.A. Nascimento Silva, and M. Panella, “Eutrophication Analysis of Water Reservoirs by Remote Sensing and Neural Networks”, Proc. of Progress in ElectRomegnetics Research Symposium (PIERS-Toyama 2018), pp. 458-463, ISBN: 978-4-8855-2316-8, ISSN: 1559-9450, DOI: 10.23919/PIERS.2018.8597731, IEEE, Toyama, Japan, 1-4 August 2018.

[C-54]   M. Panella and A. Rosato, “A Training Procedure for Quantum Random Vector Functional-link Networks”, Proc. of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2019), pp. 7973-7977, ISBN: 978-1-4799-8131-1, ISSN: 1520-6149, DOI: 10.1109/ICASSP.2019.8683532, IEEE, Brighton, U.K., 12-17 May 2019.

[C-55]   A. Rosato, R. Araneo, A. Andreotti, and M. Panella, “2-D Convolutional Deep Neural Network for Multivariate Energy Time Series Prediction”, Proc. of IEEE International Conference on Environment and Electrical Engineering and IEEE Industrial and Commercial Power Systems (EEEIC / I&CPS Europe 2019), pp. 1-4, ISBN: 978-1-7281-0653-3, DOI: 10.1109/EEEIC.2019.8783304, IEEE, Genoa, Italy, 11-14 June 2019.

[C-56]   A. Rosato, R. Araneo, A. Andreotti, and M. Panella, “Predictive Analysis of Photovoltaic Power Generation Using Deep Learning”, Proc. of IEEE International Conference on Environment and Electrical Engineering and IEEE Industrial and Commercial Power Systems (EEEIC / I&CPS Europe 2019), pp. 1-4, ISBN: 978-1-7281-0653-3, DOI: 10.1109/EEEIC.2019.8783868, IEEE, Genoa, Italy, 11-14 June 2019.

[C-57] A. Stolfi, F. Angeletti, P. Gasbarri, and M. Panella, “A deep learning strategy for on-orbit servicing via space robotic manipulator”, Proc. of International Congress of the Italian Association of Aeronautics and Astronautics (AIDAA 2019), pp. 722-734, ISBN: 978-88-943960-1-0, AIDAA, Rome, Italy, 9-12 September 2019.

[C-58] H.A. Nascimento Silva, A. Rosato, and M. Panella, “A Fuzzy Neural Network Approach to Quality Assessment of Water Reservoirs”, Proc. of PhotonIcs & Electromagnetics Research Symposium (PIERS-Spring 2019), pp. 2927-2932, ISBN: 978-1-7281-3403-1, ISSN: 1559-9450, DOI: 10.1109/PIERS-Spring46901.2019.9017525, IEEE, Rome, Italy, 17-20 June 2019.

[C-59] A. Rosato, R. Araneo, and M. Panella, “Decentralized Prediction of Electrical Time Series in Smart Grids Using Long Short-Term Memory Neural Networks”, Proc. of PhotonIcs & Electromagnetics Research Symposium (PIERS-Spring 2019), pp. 2899-2907, ISBN: 978-1-7281-3403-1, ISSN: 1559-9450, DOI: 10.1109/PIERS-Spring46901.2019.9017674, IEEE, Rome, Italy, 17-20 June 2019.

[C-60] L. Di Antonio, A. Rosato, V. Colaiuda, A. Lombardi, B. Tomassetti, and M. Panella, “Multivariate Prediction of PM10 Concentration by LSTM Neural Networks”, Proc. of PhotonIcs & Electromagnetics Research Symposium (PIERS-Fall 2019), pp. 423-431, ISBN: 978-1-7281-5304-9, ISSN: 1559-9450, DOI: 10.1109/PIERS-Fall48861.2019.9021929, IEEE, Xiamen, China, 17-20 December 2019.

[C-61] A. Rosato, R. Araneo, and M. Panella, “Multivariate Prediction in Photovoltaic Power Plants by a Stacked Deep Neural Network”, Proc. of PhotonIcs & Electromagnetics Research Symposium (PIERS-Fall 2019), pp. 451-457, ISBN: 978-1-7281-5304-9, ISSN: 1559-9450, DOI: 10.1109/PIERS-Fall48861.2019.9021584, IEEE, Xiamen, China, 17-20 December 2019.

[C-62] F. Succetti, A. Rosato, R. Araneo, and M. Panella, “Multidimensional Feeding of LSTM Networks for Multivariate Prediction of Energy Time Series”, Proc. of IEEE International Conference on Environment and Electrical Engineering and IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe 2020), pp. 1-5, ISBN: 978-1-7281-7455-6, DOI: 10.1109/EEEIC/ICPSEurope49358.2020.9160593, IEEE, Madrid (virtual), Spain, 9-12 June 2020.

[C-63] G.C. Cardarilli, R. Fazzolari, M. Matta, M. Panella, A. Rosato, and S. Spanò, “An Energy-Aware Hardware Implementation of 2D Hierarchical Clustering”, Proc. of IEEE International Conference on Environment and Electrical Engineering and IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe 2020), pp. 1-5, ISBN: 978-1-7281-7455-6, DOI: 10.1109/EEEIC/ICPSEurope49358.2020.9160773, IEEE, Madrid (virtual), Madrid (virtual), Spain, 9-12 June 2020.

[C-64] F. De Caro, A. Andreotti, R. Araneo, M. Panella, A. Vaccaro, and D. Villacci, “A Review of the Enabling Methodologies for Knowledge Discovery from Smart Grids Data”, Proc. of IEEE International Conference on Environment and Electrical Engineering and IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe 2020), pp. 1-6, ISBN: 978-1-7281-7455-6, DOI: 10.1109/EEEIC/ICPSEurope49358.2020.9160678, IEEE, Madrid (virtual), Spain, 9-12 June 2020.

[C-65] A. Rosato, F. Succetti, R. Araneo, A. Andreotti, M. Mitolo, and M. Panella, “A Combined Deep Learning Approach for Time Series Prediction in Energy Environments”, Proc. of IEEE/IAS Industrial and Commercial Power Systems Technical Conference (I&CPS 2020), pp. 1-5, ISBN:978-1-7281-7195-1, ISSN: 2158-4907, DOI: 10.1109/ICPS48389.2020.9176818, IEEE, Las Vegas (virtual), U.S.A., 29 June-28 July 2020.

[C-66] A. Rosato and M. Panella, “Time Series Prediction Using Random Weights Fuzzy Neural Networks”, Proc. of IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2020), pp. 1-6, ISBN:978-1-7281-6932-3, ISSN: 1544-5615, DOI: 10.1109/FUZZ48607.2020.9177651, IEEE, Glasgow (virtual), U.K., 19-24 July 2020.

[C-67] A. Rosato, R. Araneo, and M. Panella, “Prediction of Photovoltaic Time Series by Recurrent Neural Networks and Genetic Embedding”, Proc. of IEEE Congress on Evolutionary Computation (CEC 2020), pp. 1-8, ISBN: 978-1-7281-6929-3, DOI: 10.1109/CEC48606.2020.9185891, IEEE, Glasgow (virtual), U.K., 19-24 July 2020.

[C-68] A. Rosato, F. Succetti, M. Barbirotta, and M. Panella, “ADMM Consensus for Deep LSTM Networks”, Proc. of International Joint Conference on Neural Networks (IJCNN 2020), pp. 1-8, ISBN: 978-1-7281-6926-2, ISSN: 2161-4407, DOI: 10.1109/IJCNN48605.2020.9207512, IEEE, Glasgow (virtual), U.K., 19-24 July 2020.

[C-69] P. Iannelli, F. Angeletti, P. Gasbarri, M. Panella, and A. Rosato, “Deep Learning for local damage identification in large space structures via sensor-measured time responses”, Proc. of International Astronautical Congress (IAC 2020), pp. 1-8, Vol. 2020, ISSN: 0074-1795, International Astronautical Federation (IAF), Virtual Conference, 12-14 October 2020.

[C-70] R. Walshe, A. Koene, S. Baumann, M. Panella, L. Maglaras, and F. Medeiros, “Artificial Intelligence as Enabler for Sustainable Development”, Proc. of IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC 2021), pp. 1-7, ISBN: 978-1-6654-4963-2, ISSN: 2693-8855, DOI: 10.1109/ICE/ITMC52061.2021.9570215, IEEE, Cardiff (virtual), U.K., 21-23 June 2021.    

[C-71] F. Di Luzio, A. Rosato, F. Succetti, and M. Panella, “A Blockwise Embedding for Multi-Day-Ahead Prediction of Energy Time Series by Randomized Deep Neural Networks”, Proc. of International Joint Conference on Neural Networks (IJCNN 2021), pp. 1-7, ISBN: 978-0-7381-3366-9, ISSN: 2161-4407, DOI: 10.1109/IJCNN52387.2021.9533746, IEEE, Shenzhen (virtual), China, 18-22 July 2021.

[C-72] A. Rosato, M. Panella, and D. Kleyko, “Hyperdimensional Computing for Efficient Distributed Classification with Randomized Neural Networks”, Proc. of International Joint Conference on Neural Networks (IJCNN 2021), pp. 1-10, ISBN: 978-0-7381-3366-9, ISSN: 2161-4407, DOI: 10.1109/IJCNN52387.2021.9533805, IEEE, Shenzhen (virtual), China, 18-22 July 2021.

[C-73] F. Succetti, F. Di Luzio, A. Ceschini, A. Rosato, R. Araneo, and M. Panella, “Multivariate Prediction of Energy Time Series by Autoencoded LSTM Networks”, Proc. of IEEE International Conference on Environment and Electrical Engineering and IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe 2021), pp. 1-5, ISBN: 978-1-6654-3613-7, DOI: 10.1109/EEEIC/ICPSEurope51590.2021.9584744, IEEE, Bari, Italy, 7-10  September 2021.

[C-74] A. Ceschini, A. Rosato, F. Succetti, F. Di Luzio, M. Mitolo, R. Araneo, and M. Panella, “Deep Neural Networks for Electric Energy Theft and Anomaly Detection in the Distribution Grid”, Proc. of IEEE International Conference on Environment and Electrical Engineering and IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe 2021), pp. 1-5, ISBN: 978-1-6654-3613-7, DOI: 10.1109/EEEIC/ICPSEurope51590.2021.9584796, IEEE, Bari, Italy, 7-10 September 2021.

[C-75] R. Loggia, M. Kermani, R. Araneo, D. Borello, M. Panella, and L. Martirano, “A Hybrid Energy Hub Investigation with Renewables and Electric Vehicle in a Smart Microgrid Lab”, Proc. of IEEE International Conference on Environment and Electrical Engineering and IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe 2021), pp. 1-7, ISBN: 978-1-6654-3613-7, DOI: 10.1109/EEEIC/ICPSEurope51590.2021.9584669, IEEE, Bari, Italy, 7-10 September 2021.

[C-76] A. Ceschini, A. Rosato, F. Succetti, R. Araneo , and M. Panella, “Multivariate Time Series Analysis for Electrical Power Theft Detection in the Distribution Grid”, Proc. of IEEE International Conference on Environment and Electrical Engineering and IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe 2022), pp. 1-5, ISBN: 978-1-6654-8537-1, DOI: 10.1109/EEEIC/ICPSEurope54979.2022.9854628, IEEE, Prague, Czech Republic, June 28-July 1, 2022.

[C-77] F. Di Luzio, F. Succetti, A. Rosato, R. Araneo, and M. Panella, “A Price-aware Dynamic Decision System in Energy Communities”, Proc. of IEEE International Conference on Environment and Electrical Engineering and IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe 2022), pp. 1-6, ISBN: 978-1-6654-8537-1, DOI: 10.1109/EEEIC/ICPSEurope54979.2022.9854767, IEEE, Prague, Czech Republic, June 28-July 1, 2022.

[C-78] A. Verdone, S. Scardapane, and M. Panella, “Multi-site Forecasting of Energy Time Series with Spatio-Temporal Graph Neural Networks”, Proc. of International Joint Conference on Neural Networks (IJCNN 2022), pp. 1-8, ISBN: 978-1-7281-8671-9, ISSN: 2161-4407, DOI: 10.1109/IJCNN55064.2022.9892160, IEEE, Padua, Italy, July 18-23, 2022.

[C-79] A. Ceschini, A. Rosato, and M. Panella, “Hybrid Quantum-Classical Recurrent Neural Networks for Time Series Prediction”, Proc. of International Joint Conference on Neural Networks (IJCNN 2022), pp. 1-8, ISBN: 978-1-7281-8671-9, ISSN: 2161-4407, DOI: 10.1109/IJCNN55064.2022.9892441, IEEE, Padua, Italy, July 18-23, 2022.

[C-80] A. Rosato, M. Panella, E. Osipov, and D. Kleyko, “Few-shot Federated Learning in Randomized Neural Networks via Hyperdimensional Computing”, Proc. of International Joint Conference on Neural Networks (IJCNN 2022), pp. 1-8, ISBN: 978-1-7281-8671-9, ISSN: 2161-4407, DOI: 10.1109/IJCNN55064.2022.9892007, IEEE, Padua, Italy, July 18-23, 2022.

[C-81] B. Alam, A. Ceschini, A. Rosato, M. Panella, and R. Asquini, “All-optical AND Logic Gate Based on Semiconductor Optical Amplifiers for Implementing Deep Recurrent Neural Networks”, Proc. of International Conference on Numerical Simulation of Optoelectronic Devices (NUSOD 2022), pp. 25-26, ISBN: 978-1-6654-7899-1, ISSN: 2158-3234, DOI: 10.1109/NUSOD54938.2022.9894780, IEEE, Turin (online), Italy, September 12-16, 2022.

[C-82] M. Incudini, M. Grossi, A. Ceschini, A. Mandarino, M. Panella, S. Vallecorsa, D. Windridge, and A. Di Pierro, “Ensembling Techniques for Quantum Neural Networks”, Quantum Techniques in Machine Learning (QTML 2022), conference abstract, pp. 1-6, University of Naples Federico II, Naples, Italy, November 8-11, 2022.

[C-83] V. Eramo, F.G. Lavacca, F. Valente, V. Filippetti, A. Rosato, A. Verdone, and M. Panella, “Neural Graphs: an Effective Solution for the Resource Allocation in NFV Sites interconnected by Elastic Optical Networks”, Proc. of International Conference on Transparent Optical Networks (ICTON 2023), invited paper, pp. 1-6, ISBN: 979-8-3503-0303-2, ISSN: 2161-2064, DOI: 10.1109/ICTON59386.2023.10207206, IEEE, Bucharest, Romania, July 2-6, 2023.

[C-84] F. Scala, A. Ceschini, D. Gerace, and M. Panella, “A General Approach for Dropout in Quantum Neural Networks”, Proc. of International Conference on Quantum Techniques in Machine Learning (QTML 2023), conference abstract, pp. 1-4, CERN, Geneva, Switzerland, November 19-24, 2023.

[C-85] F. De Falco, A. Ceschini, A. Sebastianelli, M. Panella, and B. Le Saux, “Towards Quantum Diffusion Models”, Proc. of International Conference on Quantum Techniques in Machine Learning (QTML 2023), conference abstract, pp. 1-4, CERN, Geneva, Switzerland, November 19-24, 2023.

[C-86] S. Mair, A. Sebastianelli, A. Ceschini, S. Vidal, M. Panella, and B. Le Saux, “Towards Strategies to Avoid Barren Plateaus”, Proc. of International Conference on Quantum Techniques in Machine Learning (QTML 2023), conference abstract, pp. 1-4, CERN, Geneva, Switzerland, November 19-24, 2023.

[C-87] F. Succetti, A. Dell’Era, A. Rosato, A. Fioravanti, R. Araneo, and M. Panella, “A Deep Learning-based Approach for Battery Life Classification”, Proc. of IEEE International Conference on Environment and Electrical Engineering and IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe 2024), pp. 1-4, ISBN: 979-8-3503-5518-5, IEEE, Rome, Italy, June 17-20, 2024.

[C-88] A. Verdone, S. Scardapane, R. Araneo, and M. Panella, “On the Exploration of Graph State-Space Models for Spatio-Temporal Renewable Energy Forecasting”, Proc. of IEEE International Conference on Environment and Electrical Engineering and IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe 2024), pp. 1-5, ISBN: 979-8-3503-5518-5, IEEE, Rome, Italy, June 17-20, 2024.

[C-89] L. Lavagna, A. Ceschini, A. Rosato, and M. Panella, “A Layerwise-Multi-Angle Approach to Fine-Tuning the Quantum Approximate Optimization Algorithm”, Proc. of International Joint Conference on Neural Networks (IJCNN 2024), pp. 1-8, ISSN: 2161-4393, IEEE, Yokohama, Japan, June 30-July 5, 2024.

[C-90] F. Angeletti, F. Succetti, M. Panella, and A. Rosato, “A Neural Network Symbolic Approach to Structural Health Monitoring in Aerospace Applications”, Proc. of IEEE Congress on Evolutionary Computation (CEC 2024), pp. 1-8, IEEE, Yokohama, Japan, June 30-July 5, 2024.

[C-91] L. Bergadano, A. Ceschini, P. Chiavassa, E. Giusto, B. Montrucchio, M. Panella, and A. Rosato, “Q-SCALE: Quantum computing-based Sensor Calibration for Advanced Learning and Efficiency”, Proc. of IEEE International Conference on Quantum Computing and Engineering (QCE 2024), pp. 306-314, ISBN: 979-8-3315-4137-8, DOI: 10.1109/QCE60285.2024.00044, IEEE, Montreal, Canada, September 15-20, 2024.

[C-92] F. De Falco, L. Lavagna, A. Ceschini, A. Rosato, and M. Panella, “Evolving Hybrid Quantum-Classical GRU Architectures for Multivariate Time Series”, Proc. of IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2024), pp. 1-6, ISBN: 979-8-3503-7225-0, ISSN: 2161-0371, DOI: 10.1109/MLSP58920.2024.10734792, IEEE, London, U.K., September 22-25, 2024.

[C-93] L. Lavagna, F. De Falco, S. Piperno, A. Ceschini, A. Rosato, and M. Panella, “Quantum Generative Modeling via Straightforward State Preparation”, Proc. of International Conference on Quantum Techniques in Machine Learning (QTML 2024), conference abstract, pp. 1-3, University of Melbourne, Melbourne, Australia, November 25-29, 2024.

[C-94] F. De Falco, S. Piperno, L. Lavagna, A. Ceschini, A. Rosato, and M. Panella, “Enhancing QAOA Ansatz via Multi-Parameterized Layer and Blockwise Optimization”, Proc. of International Conference on Quantum Techniques in Machine Learning (QTML 2024), conference abstract, pp. 1-3, University of Melbourne, Melbourne, Australia, November 25-29, 2024.

[C-95] S. Piperno, L. Lavagna, F. De Falco, A. Ceschini, A. Rosato, D. Windridge, and M. Panella, “Quantum Enhanced Knowledge Distillation”, Proc. of International Conference on Quantum Techniques in Machine Learning (QTML 2024), conference abstract, pp. 1-3, University of Melbourne, Melbourne, Australia, November 25-29, 2024.

[C-96] F. De Falco, A. Ceschini, A. Sebastianelli, B. Le Saux, and M. Panella, “New advancements on Quantum Latent Diffusion Models”, Proc. of International Conference on Quantum Technology for High-Energy Physics (QT4HEP 2025), conference abstract, pp. 1-3, CERN, Geneva, Switzerland, January 20-24, 2025.

[C-97] E. Lopez, L. Sigillo, F. Colonnese, M. Panella, and D. Comminiello, “Guess What I Think: Streamlined EEG-to-Image Generation with Latent Diffusion Models”, Proc. of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2025), IEEE, Hyderabad, India, April 6-11, 2025.

[C-98] L. Lavagna, F. De Falco, A. Ceschini, A. Rosato, and  M. Panella, “Trade-offs in Cryptosystems by Boolean and Quantum Circuits”, Proc. of IEEE International Symposium on Circuits and Systems (ISCAS 2025), IEEE, London, U.K., May 25-28, 2025.

Italian Conference Proceedings

[I-1]   G. Martinelli and M. Panella, “Oscillatori quasi-caotici” (in Italian), in Memorie ET2001 (XVII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, p. 1, Gruppo Nazionale Ricercatori di Elettrotecnica, Catania, Italy, 06-09 September 2001.

 [I-2]   M. Panella, A. Rizzi, F. M. Frattale Mascioli, and G. Martinelli, “Ottimizzazione costruttiva di reti neurali per il clustering gerarchico” (in Italian), in Memorie ET2001 (XVII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, p. 1, Gruppo Nazionale Ricercatori di Elettrotecnica, Catania, Italy, 06-09 September 2001.

[I-3]   F.M. Frattale Mascioli, M. Panella, G. Martinelli, and A. Rizzi, “Ottimizzazione di classificatori non-esclusivi per l’elaborazione del segnale musicale” (in Italian), in Memorie ET2001 (XVII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, p. 1, Gruppo Nazionale Ricercatori di Elettrotecnica, Catania, Italy, 06-09 September 2001.

[I-4]   A. Rizzi, M. Panella, F. M. Frattale Mascioli, and G. Martinelli, “Reti neurofuzzy Min-Max a risoluzione adattativa per la classificazione” (in Italian), in Memorie ET2001 (XVII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Catania, Italy, 06-09 September 2001.

[I-5]   G. Martinelli, F. M. Frattale Mascioli, A. Rizzi, and M. Panella, “Reti Neurofuzzy per il Modellamento Data Driven: Approssimazione Funzionale e Predizione” (in Italian), in Memorie ET2002 (XVIII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Messina, Italy, 27-29 June 2002.

[I-6]   G. Martinelli, F. M. Frattale Mascioli, A. Rizzi, and M. Panella, “Reti Neurofuzzy per il Modellamento Data Driven: Classificazione e Clustering” (in Italian), in Memorie ET2002 (XVIII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Messina, Italy, 27-29 June 2002.

[I-7]   R. Colicchia, F. M. Frattale Mascioli, T. Valentinetti, and M. Panella, “Nuove tecniche per l’elaborazione predittiva dei dati ambientali” (in Italian), in Atti della Giornata di Studio sulle Tecnologie Elettriche nel Rispetto del Territorio, Università degli Studi di Rome “La Sapienza”, conference abstract, pp. 1-11, Sezione AEI di Roma, Enel Distribuzione S.p.A., Rome, Italy, 21 June 2002.

[I-8]   A. Rizzi, F.M. Frattale Mascioli, and M. Panella, “Applicazione di classificatori neurofuzzy alla diagnostica di cavi in media tensione” (in Italian), in Memorie ET2003 (XIX Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Perugia, Italy, 18-21 June 2003.

[I-9]   G. Martinelli, M. Panella, E. Di Claudio, F.M. Frattale Mascioli, and A. Rizzi, “Circuiti di potenza per lo smorzamento di vibrazioni meccaniche tramite trasduttori piezoelettrici” (in Italian), in Memorie ET2003 (XIX Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Perugia, Italy, 18-21 June 2003.

 [I-10]   M. Panella and G. Martinelli, “Circuiti RNS per la realizzazione di modulatori quasi-caotici” (in Italian), in Memorie ET2003 (XIX Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Perugia, Italy, 18-21 June 2003.

[I-11]   F.M. Frattale Mascioli, M. Panella, A. Rizzi, and G. Martinelli, “Reti neurali e neurofuzzy per la predizione e la codifica robusta di serie caotiche naturali” (in Italian), in Memorie ET2003 (XIX Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Perugia, Italy, 18-21 June 2003.

[I-12]   F.M. Frattale Mascioli, G. Martinelli, M. Panella, and A. Rizzi, “Applicazione delle reti neurofuzzy alla diagnostica dell'isolamento di cavi per la trasmissione e distribuzione dell’energia elettrica” (in Italian), in Memorie ET2004 (XX Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Salerno, Italy, 16-19 June 2004.

[I-13]   G. Martinelli, F.M. Frattale Mascioli, M. Panella, M. Porfiri, and M. Paschero, “Sintesi di circuiti autoalimentati a capacità negativa per lo smorzamento di vibrazioni meccaniche mediante trasduttori piezoelettrici” (in Italian), in Memorie ET2004 (XX Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Salerno, Italy, 16-19 June 2004.

[I-14]   G. Martinelli, M. Panella, and T. Loreto, “Ottimizzazione distribuita per imitazione biologica” (in Italian), in Memorie ET2005 (XXI Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, p. 1, Gruppo Nazionale Ricercatori di Elettrotecnica, Rome, Italy, 16-19 June 2005.

[I-15]   F.M. Frattale Mascioli, M. Panella, and A. Rizzi, “Reti neurali per l’acquisizione e l’analisi dei dati nel campo dell’infomobilità” (in Italian), in Memorie ET2005 (XXI Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Rome, Italy, 16-19 June 2005.

[I-16]   M. Panella, F.M. Frattale Mascioli, G. Martinelli, and M. Paschero, “Sintesi di circuiti e reti neurali per il controllo delle informazioni in una rete di sensori” (in Italian), in Memorie ET2005 (XXI Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Rome, Italy, 16-19 June 2005.

[I-17]   G. Martinelli and M. Panella, “Circuiti quantistici e reti neurali quantistiche” (in Italian), in Memorie ET2006 (XXII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, p. 1, Gruppo Nazionale Ricercatori di Elettrotecnica, Turin, Italy, 15-17 June 2006.

[I-18]   M. Panella, F.M. Frattale Mascioli, M. Paschero, and G. Martinelli, “Sintesi di circuiti intelligenti per il controllo di sistemi ibridi” (in Italian), in Memorie ET2006 (XXII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Turin, Italy, 15-17 June 2006.

[I-19]   Albenzio Cirillo, Raffaele Parisi, Massimo Panella, and Aurelio Uncini, “Localizzazione di sorgenti sonore in ambienti riveberanti” (in Italian), in Memorie ET2007 (XXIII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, p. 1, Gruppo Nazionale Ricercatori di Elettrotecnica, Florence, Italy, 28-30 June 2007.

[I-20]   M. Panella, “Reti neurofuzzy per il controllo e l'assistenza in tempo reale alla guida dei veicoli” (in Italian), in Memorie ET2007 (XXIII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Florence, Italy, 28-30 June 2007.

[I-21]   G. Martinelli, M. Panella, and A. Rizzi, “Reti neurali, neurofuzzy e memorie associative quantistiche” (in Italian), in Memorie ET2007 (XXIII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, p. 1, Gruppo Nazionale Ricercatori di Elettrotecnica, Florence, Italy, 28-30 June 2007.

[I-22]   M. Panella, “Analisi simbolica ed ottimizzazione circuitale di sistemi piezo-elettromeccanici” (in Italian), in Memorie ET2008 (XXIV Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, invited talk, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Pavia, Italy, 19-21 June 2008.

[I-23]   G. Martinelli, M. Panella, and A. Rizzi, “Ottimizzazione per imitazione: dal calcolo evolutivo al calcolo quantistico” (in Italian), in Memorie ET2008 (XXIV Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Pavia, Italy, 19-21 June 2008.

[I-24]   M. Panella, “Circuiti Quantistici per la Realizzazione di Nuove Tecniche di Imaging Diagnostico” (in Italian), in Memorie ET2010 (XXVI Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Naples, Italy, 9-11 June 2010.

[I-25]   Massimo Panella and Francesco Barcellona, “Reti neurali per la predizione delle dinamiche dei prezzi delle commodity energetiche” (in Italian), in Memorie ET2011 (XXVII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Bologna, Italy, 15-17 June 2011.

[I-26]   Massimo Panella and Francesco Barcellona, “Computational intelligence per il modellamento del mercato delle commodity energetiche” (in Italian), in Memorie ET2012 (XXVIII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Taormina (ME), Italy, 20-22 June 2012.

[I-27]   Massimo Panella, Marco Maisto, Marco Barbato, Luca Liparulo, and Andrea Proietti, “Algoritmi di riconoscimento e applicazioni basate su smart cameras e telecamere RGB-D” (in Italian), in Memorie ET2013 (XXIX Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Padua, Italy, 20-21 June 2013.

[I-28]   Luca Liparulo, Massimo Panella, and Andrea Proietti, “Reti neurali e logica fuzzy per il modellamento di sistemi complessi in contesti reali” (in Italian), in Memorie ET2013 (XXIX Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Padua, Italy, 20-21 June 2013.

[I-29]   A. Proietti, L. Liparulo, M. Barbato, and M. Panella, “Tecniche di intelligenza computazionale per rilevazione e analisi di depositi di polvere in ambienti museali” (in Italian), in Memorie ET2014 (XXX Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Sorrento (NA), Italy, 19-20 June 2014.

[I-30]   L. Liparulo, A. Proietti, M. Maisto, and M. Panella, “Tecniche di pattern recognition per l’elaborazione di dati provenienti da sensori inerziali (IMU)” (in Italian), in Memorie ET2014 (XXX Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Sorrento (NA), Italy, 19-20 June 2014.

[I-31]   L. Liparulo, A. Proietti, R. Altilio, and M. Panella, “Tecniche di fuzzy pattern recognition per l’elaborazione di dati provenienti da elettromiografia di superficie (sEMG)” (in Italian), in Memorie ET2015 (XXXI Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Genoa, Italy, 18-19 June 2015.

[I-32]   A. Proietti, L. Liparulo, and M. Panella, “Fuzzy clustering per l’analisi di dati tramite modelli geometrici non vincolati e funzioni di appartenenza basate su kernel” (in Italian), in Memorie ET2015 (XXXI Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Genoa, Italy, 18-19 June 2015.

[I-33]   S. Scardapane, R. Altilio, R. Fierimonte, A. Uncini, and M. Panella, “Apprendimento distribuito di reti neurali e neurofuzzy” (in Italian), in Memorie ET2016 (XXXII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Palermo, Italy, 15-17 June 2016.

[I-34]   A. Proietti, A. Rosato, H.A. Nascimento Silva, and M. Panella, “Machine learning per l’analisi ambientale” (in Italian), in Memorie ET2016 (XXXII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Palermo, Italy, 15-17 June 2016.

[I-35]   R. Altilio, L. Liparulo, M. Barbato, and M. Panella, “Tecniche di intelligenza computazionale applicate alla riabilitazione motoria” (in Italian), in Memorie ET2016 (XXXII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Palermo, Italy, 15-17 June 2016.

[I-36]   R. Altilio, G. Andreasi, and M. Panella, “Tecniche di pattern recognition applicate alla riabilitazione motoria” (in Italian), in Memorie ET2017 (XXXIII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Milan, Italy, 29-30 June 2017.

[I-37]   M. Panella, R. Altilio, and A. Rosato, “Apprendimento di reti neurali in circuiti a precisione numerica finita” (in Italian), in Memorie ET2017 (XXXIII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Milan, Italy, 29-30 June 2017.

[I-38]   A. Rosato, R. Altilio, R. Araneo, and M. Panella, “Reti neurali e logica fuzzy per la predizione di serie energetiche” (in Italian), in Memorie ET2017 (XXXIII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Milan, Italy, 29-30 June 2017.

[I-39]   S. Scardapane, D. Comminiello, M. Scarpiniti, M. Panella, and A. Uncini, “Apprendimento distribuito in scenari single-task e multi-task” (in Italian), in Memorie ET2017 (XXXIII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Milan, Italy, 29-30 June 2017.

[I-40]   R. Altilio, A. Rosato, and M. Panella, “Apprendimento sparso di reti neurofuzzy” (in Italian), in Memorie ET2018 (XXXIV Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Rome, Italy, 14-15 June 2018.

[I-41]   M. Panella, R. Altilio, and A. Rosato, “Apprendimento on-line di reti neurali su architetture a precisione numerica finita” (in Italian), in Memorie ET2018 (XXXIV Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Rome, Italy, 14-15 June 2018.

[I-42]   M. Panella and A. Rosato, “Reti neurali quantistiche random vector functional-link” (in Italian), in Memorie ET2019 (XXXV Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Viterbo, Italy, 20-21 June 2019.

[I-43]   A. Rosato, R. Araneo, and M. Panella, “deep learning per il controllo predittivo nella gestione delle risorse energetiche distribuite” (in Italian), in Memorie ET2019 (XXXV Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Viterbo, Italy, 20-21 June 2019.

[I-44] M. Panella and A. Proietti, “Intelligenza artificiale per l’offerta di servizi turistici personalizzati” (in Italian), in Atti del 2° Convegno Annuale del Distretto Tecnologico Beni e Attivtà Culturali (DTC) Lazio – Centro di Eccellenza, conference abstract, “L'Erma” di Bretschneider, Rome, Italy, November 4, 2021.

[I-45] A. Ceschini, A. Rosato, and M. Panella, “Reti neurali quantistiche per dispositivi Noisy Intermediate-Scale Quantum (NISQ)” (in Italian), in Memorie ET2022 (XXXVI Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Ancona, Italy, June 23-24, 2022.

[I-46] F. Di Luzio, A. Rosato, and M. Panella, “Reti neurali randomizzate per la predizione di serie energetiche” (in Italian), in Memorie ET2022 (XXXVI Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Ancona, Italy, June 23-24, 2022.

[I-47] A. Rosato and M. Panella, “Calcolo iperdimensionale e architetture a vettori simbolici per le reti neurali” (in Italian), in Memorie ET2022 (XXXVI Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Ancona, Italy, June 23-24, 2022.

[I-48] F. Succetti, A. Rosato, R. Araneo, and M. Panella, “Deep learning per la predizione multivariata di serie energetiche” (in Italian), in Memorie ET2022 (XXXVI Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Ancona, Italy, June 23-24, 2022.

[I-49] A. Verdone, S. Scardapane, and M. Panella, “Spatiotemporal graph neural network per energy forecasting e anomaly detection” (in Italian), in Memorie ET2022 (XXXVI Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Ancona, Italy, June 23-24, 2022.

[I-50] B. Alam, A. Ceschini, A. Rosato, M. Panella, and R. Asquini, “All-optical logic gates based on semiconductor optical amplifiers for implementing deep recurrent neural networks”, in Atti della 53.ma Riunione Annuale dell’Associazione Società Italiana di Elettronica (SIE), conference abstract, pp. 1-2, Associazione Società Italiana di Elettronica, Pizzo (VV), Italy, September 7-9, 2022.

[I-51] A. Ceschini, L. Lavagna, F. De Falco, A. Rosato, and M. Panella, “Convergenza e generalizzazione nelle reti neurali quantistiche” (in Italian), in Memorie ET2024 (XXXVIII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Bari, Italy, June 19-21, 2024.

[I-52] F. De Falco, A. Ceschini, A. Rosato, and M. Panella, “Modelli generativi quantistici” (in Italian), in Memorie ET2024 (XXXVIII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Bari, Italy, June 19-21, 2024.

[I-53] F. Di Luzio, F. Colonnese, A. Rosato, and M. Panella, “Reti neurali applicate all’elaborazione di segnali biomedici per l’analisi comportamentale” (in Italian), in Memorie ET2024 (XXXVIII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Bari, Italy, June 19-21, 2024.

[I-54] V. Mottola, A. Ceschini, M. Panella, and A. Tamburrino, “Il quantum computing per la tomografia elettromagnetica” (in Italian), in Memorie ET2024 (XXXVIII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Bari, Italy, June 19-21, 2024.

[I-55] A. Rosato and M. Panella, “Integrazione del calcolo iperdimensionale nei circuiti digitali e nelle reti neurali” (in Italian), in Memorie ET2024 (XXXVIII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Bari, Italy, June 19-21, 2024.

[I-56] F. Succetti, A. Rosato, and M. Panella, “Reti neurali e neurofuzzy per la classificazione di serie temporali energetiche” (in Italian), in Memorie ET2024 (XXXVIII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Bari, Italy, June 19-21, 2024.

[I-57] A. Verdone, S. Scardapane, and M. Panella, “Temporal Graph Neural Networks and Explainability for Future Energy Scenarios” (in Italian), in Memorie ET2024 (XXXVIII Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Bari, Italy, June 19-21, 2024.

[I-58] A. Ceschini and M. Panella, “Advancing Quantum Machine Learning: Efficient Hybrid Quantum Computation”, in Quantum Computing Annual Meeting ICSC - Spoke 10, Research and Innovation, conference abstract, poster, National Research Centre for High Performance Computing, Big Data and Quantum Computing (ICSC), Milano, Italy, September 3-5, 2024.

[I-59] A. Ceschini, L. Lavagna, F. De Falco, A. Rosato, and M. Panella, “Circuiti neurali quantistici per il processamento di grafi, immagini e serie temporali” (in Italian), in Memorie ET2025 (XXXIX Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Villasimius (Cagliari), Italy, June 12-13, 2025.

[I-60] F. De Falco, A. Ceschini, A. Rosato, and M. Panella, “Studio di modelli generativi quantistici” (in Italian), in Memorie ET2025 (XXXIX Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Villasimius (Cagliari), Italy, June 12-13, 2025.

[I-61] F. Di Luzio, F. Colonnese, S. Colella, A. Rosato, and M. Panella, “Algoritmi basati su reti neurali per l’analisi comportamentale attraverso l’elaborazione di segnali biometrici” (in Italian), in Memorie ET2025 (XXXIX Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Villasimius (Cagliari), Italy, June 12-13, 2025.

[I-62] L. Lavagna, A. Ceschini, S. Piperno, M. Casalbore, A. Rosato, and M. Panella, “Soluzioni quantistico-classiche per ottimizzazione e rilevamento di anomalie” (in Italian), in Memorie ET2025 (XXXIX Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Villasimius (Cagliari), Italy, June 12-13, 2025.

[I-63] S. Piperno, G. Vittori, A. Rosato, and M. Panella, “Distillazione della conoscenza quantistica” (in Italian), in Memorie ET2025 (XXXIX Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Villasimius (Cagliari), Italy, June 12-13, 2025.

[I-64] A. Rosato, L. Lavagna, and M. Panella, “Integrazione del calcolo iperdimensionale nei circuiti digitali, nelle reti neurali e nelle architetture computazionali quantistiche” (in Italian), in Memorie ET2025 (XXXIX Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Villasimius (Cagliari), Italy, June 12-13, 2025.

[I-65] F. Succetti, A. Rosato, R. Araneo, and M. Panella, “Reti neurali profonde per la classificazione dello stato di vita delle batterie” (in Italian), in Memorie ET2025 (XXXIX Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Villasimius (Cagliari), Italy, June 12-13, 2025.

[I-66] A. Verdone, S. Scardapane, R. Araneo, and M. Panella, “Predizione delle energie rinnovabili in applicazioni a siti multipli attraverso reti neurali a grafo” (in Italian), in Memorie ET2025 (XXXIX Riunione Annuale dei Ricercatori di Elettrotecnica), conference abstract, pp. 1-2, Gruppo Nazionale Ricercatori di Elettrotecnica, Villasimius (Cagliari), Italy, June 12-13, 2025.

Book Chapters

[B-1]   F.M. Frattale Mascioli, A. Mancini, A. Rizzi, M. Panella, and G. Martinelli, “Neurofuzzy Approximator based on Mamdani's Model”, in Neural Nets WIRN Vietri-01 (R. Tagliaferri and M. Marinaro Eds.), Perspectives in Neural Computing, pp. 23-59, ISBN: 1-85233-505-X, 9781852335052, ISSN: 1431-6854, Springer-Verlag, U.K., 2002.

[B-2]   P. Burrascano, S. Fiori, F.M. Frattale Mascioli, G. Martinelli, M. Panella, and A. Rizzi, “Visual Path Following and Obstacle Avoidance by Artificial Neural Networks”, in Enabling technologies for the PRASSI autonomous robot (S. Taraglio and V. Nanni Eds.), pp. 30-39, ISBN: 88-8286-024-8, ENEA Research Institute, Rome, Italy, 2002.

[B-3]   G. Martinelli, F.M. Frattale Mascioli, M. Panella, and A. Rizzi, “Extended Random Neural Networks”, in Neural Nets (WIRN VIETRI 2002, M. Marinaro and R. Tagliaferri Eds.), Lecture Notes in Computer Science, Vol. 2486, pp. 75-82, ISBN: 978-3-540-44265-3, ISSN: 0302-9743, DOI: 10.1007/3-540-45808-5_7, Springer-Verlag, Germany, 2002.

[B-4]   M. Panella, “VLSI Architectures for the Generation of Quasi-chaotic Behavior”, invited chapter in Recent Research Developments in Electronics (S.G. Pandalai Ed.), Vol. 1, pp. 67-89, ISBN: 81-7895-068-5, Transworld Research Network, India, 2002.

[B-5]   M. Panella, F.M. Frattale Mascioli, A. Rizzi, and G. Martinelli, “A New ANFIS Synthesis Approach for Time Series Forecasting”, in Soft Computing Applications (WILF 2001, A. Bonarini, F. Masulli, and G. Pasi Eds.), Advances in Soft Computing, pp. 59-69, ISBN: 3-7908-1544-6, ISSN: 1615-3871, Physica-Verlag, Germany, 2003.

[B-6]   M. Panella, F.M. Frattale Mascioli, A. Rizzi, and G. Martinelli, “ANFIS Synthesis by Hyperplane Clustering for Time Series Prediction”, in Neural Nets (WIRN VIETRI 2003, B. Apolloni, M. Marinaro, and R. Tagliaferri Eds.), Lecture Notes in Computer Science, Vol. 2859, pp. 77-84, ISBN: 978-3-540-20227-1, ISSN: 0302-9743, DOI: 10.1007/978-3-540-45216-4_8, Springer-Verlag, Germany, 2003.

[B-7]   F. Barcellona, F. Filippi, M. Panella, A.M. Bersani, and A. Alessandrini, “Neural Processing of Biomedical Data for Improving Driving Safety”, in Modelling in Medicine and Biology VI (M. Ursino, C.A. Brebbia, G. Pontrelli, and E. Magosso Eds.), WIT Transactions on Biomedicine and Health, Vol. 8, pp. 213-219, ISBN: 1-84564-024-1, ISSN (Print): 1747-4485, ISSN (On-Line): 1743-3525, WIT Press, U.K., 2005.

[B-8]   M. Panella, G. Grisanti, and A. Rizzi, “A Probabilistic PCA Clustering Approach to the SVD Estimate of Signal Subspaces”, in Biological and Artificial Intelligence Environments (WIRN VIETRI 2004, B. Apolloni, M. Marinaro, and R. Tagliaferri Eds.), pp. 271-279, ISBN: 978-1-4020-3431-2, DOI: 10.1007/1-4020-3432-6_32, Springer, The Netherlands, 2005.

[B-9]   M. Panella, F. Barcellona, and A.M. Bersani, “Neural Network in Modeling Glucose-Insulin Behavior”, in Biological and Artificial Intelligence Environments (WIRN VIETRI 2004, B. Apolloni, M. Marinaro, and R. Tagliaferri Eds.), pp. 367-374, ISBN: 978-1-4020-3431-2, DOI: 10.1007/1-4020-3432-6_43, Springer, The Netherlands, 2005. 

[B-10]   M. Panella, A. Rizzi, F.M. Frattale Mascioli, and G. Martinelli, “A neuro-fuzzy system for the prediction of the vehicle traffic flow”, in Fuzzy Logic and Applications (WILF 2003, V. Di Gesù, F. Masulli, and A. Petrosino Eds.), Lecture Notes in Artificial Intelligence/Lecture Notes in Computer Science, Vol. 2955, pp. 110-118, ISBN: 978-3-540-31019-8, ISSN: 0302-9743, DOI: 10.1007/10983652_15, Springer, Germany, 2006.

[B-11]   M. Panella and G. Martinelli, “Binary Neuro-Fuzzy Classifiers Trained by Nonlinear Quantum Circuits”, in Applications of Fuzzy Sets Theory (WILF 2007, F. Masulli, S. Mitra, and G. Pasi Eds.), Lecture Notes in Artificial Intelligence/Lecture Notes in Computer Science, Vol. 4578, pp. 237-244, ISBN: 978-3-540-73399-7, ISSN: 0302-9743, DOI: 10.1007/978-3-540-73400-0_29, Springer-Verlag, Germany, 2007.

[B-12]   F.M. Frattale Mascioli, A. Rizzi, M. Panella, and C. Bettiol, “Optimization of Hybrid Electric Cars by Neuro-Fuzzy Networks”, in Applications of Fuzzy Sets Theory (WILF 2007, F. Masulli, S. Mitra, and G. Pasi Eds.), Lecture Notes in Artificial Intelligence/Lecture Notes in Computer Science, Vol. 4578, pp. 253-260, ISBN: 978-3-540-73399-7, ISSN: 0302-9743, DOI: 10.1007/978-3-540-73400-0_31, Springer-Verlag, Germany, 2007.

[B-13]   M. Panella, “Exploiting Quantum Entanglement and Quantum Superposition for Nature-Inspired Optimization”, invited chapter in Quantum Entanglement (Annalynn M. Moran Ed.), pp. 249-264, ISBN: 978-1-61761-814-7, Nova Science Publishers Inc., U.S.A., 2012.

[B-14]   M. Panella, “Complessità algoritmica” (in Italian), lemma enciclopedico in: Informatica, Vol. I, p. 203, ISBN: 9788812000784, Istituto della Enciclopedia Italiana - Treccani, Rome, Italy, 2012.

[B-15]   M. Panella, “Soft computing” (in Italian), lemma enciclopedico in: Informatica, Vol. II, p. 455, ISBN: 9788812000784, Istituto della Enciclopedia Italiana - Treccani, Rome, Italy, 2012.

[B-16]   M. Panella, L. Liparulo, and A. Proietti, “Time Series Analysis by Genetic Embedding and Neural Network Regression”, in Advances in Neural Networks: Computational and Theoretical Issues (WIRN 2014, S. Bassis, A. Esposito, and F.C. Morabito, Eds.), Smart Innovation, Systems and Technologies, Vol. 37, pp. 21-29, ISBN: 978-3-319-18163-9, ISSN: 2190-3018, DOI: 10.1007/978-3-319-18164-6_3, Springer International Publishing, Switzerland, 2015.

[B-17]   A. Rosato, R. Altilio, and M. Panella, “Recent Advances on Distributed Unsupervised Learning”, in Advances in Neural Networks: Computational Intelligence for ICT (WIRN 2015, S. Bassis, A. Esposito, F.C. Morabito, and E. Pasero, Eds.), Smart Innovation, Systems and Technologies, Vol. 54, pp. 77-86, ISBN: 978-3-319-33746-3, ISSN: 2190-3018, DOI: 10.1007/978-3-319-33747-0_8, Springer International Publishing, Switzerland, June 2016.

[B-18]   R. Fierimonte, S. Scardapane, M. Panella, and A. Uncini, “A Comparison of Consensus Strategies for Distributed Learning of Random Vector Functional-Link Networks”, in Advances in Neural Networks: Computational Intelligence for ICT (WIRN 2015, S. Bassis, A. Esposito, F.C. Morabito, and E. Pasero, Eds.), Smart Innovation, Systems and Technologies, Vol. 54, pp. 143-152, ISBN: 978-3-319-33746-3, ISSN: 2190-3018, DOI: 10.1007/978-3-319-33747-0_14, Springer International Publishing, Switzerland, June 2016.

[B-19]   S. Scardapane, R. Altilio, V. Ciccarelli, A. Uncini, and M. Panella, “Privacy-Preserving Data Mining for Distributed Medical Scenarios”, in Multidisciplinary Approaches to Neural Computing (WIRN 2016, A. Esposito, M. Faundez-Zanuy, F.C. Morabito, and E. Pasero, Eds.), Smart Innovation, Systems and Technologies, Vol. 69, pp. 119-128, ISBN: 978-3-319-56903-1, ISSN: 2190-3018, DOI: 10.1007/978-3-319-56904-8_12, Springer International Publishing, Switzerland, 2018.

[B-20]   R. Altilio, G. Andreasi, and M. Panella, “A Classification Approach to Modeling Financial Time Series”, in Neural Advances in Processing Nonlinear Dynamic Signals (WIRN 2017, A. Esposito, M. Faundez-Zanuy, F.C. Morabito, and E. Pasero, Eds.), Smart Innovation, Systems and Technologies, Vol. 102, pp. 97-106, ISBN: 978-3-319-95097-6, ISSN: 2190-3018, DOI: 10.1007/978-3-319-95098-3_9, Springer International Publishing, Switzerland, 2019.

[B-21] P. Russo and M. Panella, “Inverse Classification for Military Decision Support System”, in Neural Approaches to Dynamics of Signal Exchanges (WIRN 2018, A. Esposito, M. Faundez-Zanuy, F.C. Morabito, and E. Pasero, Eds.), Smart Innovation, Systems and Technologies, Vol. 151, pp. 157-166, ISBN 978-981-13-8949-8, ISSN: 2190-3018, DOI: 10.1007/978-981-13-8950-4_15, Springer Nature, Singapore, 2020.

[B-22] A. Rosato, M. Panella, E. Osipov, and D. Kleyko, “On Effects of Compression with Hyperdimensional Computing in Distributed Randomized Neural Networks”, in Advances in Computational Intelligence (IWANN 2021, I. Rojas, G. Joya, and A. Catala, Eds.), Lecture Notes in Computer Science, Vol. 12862, pp. 155-167, ISBN: 978-3-030-85098-2, ISSN: 0302-9743, DOI: 10.1007/978-3-030-85099-9_13, Springer Nature, Switzerland, 2021.

[B-23] F. Succetti, A. Ceschini, F. Di Luzio, A. Rosato, and M. Panella, “Time Series Prediction with Autoencoding LSTM Networks”, in Advances in Computational Intelligence (IWANN 2021, I. Rojas, G. Joya, and A. Catala, Eds.), Lecture Notes in Computer Science, Vol. 12862, pp. 306-317, ISBN: 978-3-030-85098-2, ISSN: 0302-9743, DOI: 10.1007/978-3-030-85099-9_25, Springer Nature, Switzerland, 2021.

[B-24] F. Di Luzio, F. Colonnese, A. Rosato, and M. Panella, “Detection of Autism Spectrum Disorder by a Fast Deep Neural Network”, in Applied Intelligence and Informatics (AII 2022, M. Mahmud, C. Ieracitano, M. Shamin Kaiser, N. Mammone, and F.C. Morabito, Eds.), Communications in Computer and Information Science, Vol. 1724, pp. 539-553, ISBN: 978-3-031-24800-9, ISSN: 1865-0929, DOI: 10.1007/978-3-031-24801-6_38, Springer Nature, Switzerland, 2022.

[B-25] F. Succetti, A. Rosato, and M. Panella, “Nonexclusive Classification of Household Appliances by Fuzzy Deep Neural Networks”, in Applied Intelligence and Informatics (AII 2022, M. Mahmud, C. Ieracitano, M. Shamin Kaiser, N. Mammone, and F.C. Morabito, Eds.), Communications in Computer and Information Science, Vol. 1724, pp. 404-418, ISBN: 978-3-031-24800-9, ISSN: 1865-0929, DOI: 10.1007/978-3-031-24801-6_29, Springer Nature, Switzerland, 2022.

[B-26] V. Lucaferri, M. Radicioni, F. De Lia, A. Laudani, R. Lo Presti, G.M. Lozito, F. Riganti Fulginei, M. Panella, and R. Schioppo, “An Indirect Approach to Forecast Produced Power on Photovoltaic Plants Under Uneven Shading Conditions”, in Applied Intelligence and Informatics (AII 2022, M. Mahmud, C. Ieracitano, M. Shamin Kaiser, N. Mammone, and F.C. Morabito, Eds.), Communications in Computer and Information Science, Vol. 1724, pp. 29-43, ISBN: 978-3-031-24800-9, ISSN: 1865-0929, DOI: 10.1007/978-3-031-24801-6_3, Springer Nature, Switzerland, 2022.

[B-27] B. Alam, A. Ceschini, A. Rosato, M. Panella, and R. Asquini, “Analysis of Logic Schemes for the Optical Implementation of Pointwise Operations in Gated Recurrent Unit Cells”, in Sensors and Microsystems (AISEM 2022, G. Di Francia, and C. Di Natale, Eds.), Lecture Notes in Electrical Engineering, Vol. 999, pp. 167-173, ISBN: 978-3-031-25705-6, ISSN: 1876-1100, DOI: 10.1007/978-3-031-25706-3_27, Springer Nature, Switzerland, 2023.

[B-28] F. Di Luzio, A. Paiardini, F. Colonnese, A. Rosato, and M. Panella “A Deep Neural Network for G-Quadruplexes Binding Proteins Classification”, in Advances in Computational Intelligence (IWANN 2023, I. Rojas, G. Joya, and A. Catala, Eds.), Lecture Notes in Computer Science, Vol. 14134, pp. 517-528, ISBN: 978-3-031-43084-8, ISSN: 0302-9743, DOI: 10.1007/978-3-031-43085-5_41, Springer Nature, Switzerland, 2023.

[B-29] F. Colonnese, F. Di Luzio, A. Rosato, and M. Panella, “Fast Convolutional Analysis of Task-Based fMRI Data for ADHD Detection”, in Advances in Computational Intelligence (IWANN 2023, I. Rojas, G. Joya, and A. Catala, Eds.), Lecture Notes in Computer Science, Vol. 14135, pp. 364-375, ISBN: 978-3-031-43077-0, ISSN: 0302-9743, DOI: 10.1007/978-3-031-43078-7_30, Springer Nature, Switzerland, 2023.

[B-30] A. Verdone, A. Devoto, C. Sebastiani, J. Carmignani, M. D’Onofrio, S. Giagu, S. Scardapane, and M. Panella, “Enhancing High-Energy Particle Physics Collision Analysis through Graph Data Attribution Techniques”, in WIRN 2024, A. Esposito, M. Faundez-Zanuy, F.C. Morabito, and E. Pasero, Eds., Smart Innovation, Systems and Technologies, ISSN: 2190-3018, Springer Nature, Singapore, in press.

[B-31] F. Colonnese, F. Di Luzio, S. Colella, and M. Panella, “Explaining Autism Detection by Deep Learning through Eye Gaze Patterns and Integrated Gradients”, in WIRN 2024, A. Esposito, M. Faundez-Zanuy, F.C. Morabito, and E. Pasero, Eds., Smart Innovation, Systems and Technologies, ISSN: 2190-3018, Springer Nature, Singapore, in press.

Books

[L-1]   M. Panella, Ottimizzazione strutturale di reti neurofuzzy (in Italian), Ph.D. Thesis, pp. 1- 152, University of Rome “La Sapienza”, Rome, Italy, June 2002.

[L-2]   M. Panella and A. Rizzi, Esercizi di Elettrotecnica (in Italian), pp. 1-276, ISBN: 978-88-7488-237-3, Società Editrice Esculapio, Bologna, Italy, October 2007.

[L-3]   R. Besson, S. Cavallini, G. Orlandi, M. Panella, F. Piazza, and M. Scarpiniti, Il Sistema Radiocinetelevisivo e le Competenze Territoriali (in Italian), pp. 1-212, ISBN: 88-904639-0-2, Editoriale Blu S.r.l., Rome, Italy, December 2009.

[L-4]   L. Basset, R. Besson, G. Orlandi, and M. Panella, ARTURA Tecnologia per l’arte e la natura. Le tecnologie ICT e multimediali per la valorizzazione dei beni culturali di un piccolo centro  (in Italian), pp. 1-116, ISBN: 978-88-904639-2-1, Editoriale Blu S.r.l., Rome, Italy, December 2010.

[L-5]   R. Besson, L. Liparulo, G. Orlandi, M. Panella, G.M. Poscetti, A. Proietti, and T. Vincenti, ICT e multimedialità per la cultura e il territorio – Il sistema tecnologico ARTURA 2 (in Italian), pp. 1-128, ISBN: 978-88-904639-3-8, Editoriale Blu srl, Rome, Italy, July 2012.

[L-6]   M. Panella and A. Rizzi, Esercizi di Elettrotecnica (second edition, in Italian), pp. 1-331, ISBN: 978-88-7488-804-7, Società Editrice Esculapio, Bologna, Italy, September 2014.

[L-7]   M. Barbato, G. Giaconi, L. Liparulo, M. Maisto, M. Panella, A. Proietti, and G. Orlandi, Smart devices and environments. Enabling technologies and systems for the Internet of Things, Vol. 1, pp. 1-42, ISBN: 9788826706306, Maia edizioni, Rome, Italy, December 2014.

[L-8]   M. Barbato, G. Orlandi, and M. Panella, Real-time Identification and Tracking Using Kinect. Multimodal Interaction and Performance Analysis, Vol. 2, pp. 1-37, ISBN: 9788826706313, Maia edizioni, Rome, Italy, December 2014.

[L-9]   M. Panella and A. Rizzi, Esercizi di Elettrotecnica (third edition, in Italian), pp. 1-373, ISBN: 978-88-9385-287-6, Società Editrice Esculapio, Bologna, Italy, March 2022.

Patents

[P-1]   M. Panella and F. Barcellona, “ContoGiusto”, registered software at SIAE (“Registro pubblico per il software”), n. 008585-D007773, 16 November 2012.

[P-2]   E. Pucci e M. Panella, “Life Biometric Recognition (LBR)”, registered software at SIAE (“Registro pubblico per il software”), n. 014174-D013213, 30 December 2019.

[P-3]  M. Panella, E. Pucci, and A. Rosato, “Metodo per riconoscere un corpo vivente”, industrial invention patent (IT Italy) n. 102019000012852 of 13 July 2021.

[P-4]  G. Lais, M. Panella, D. Romanini, A. Rosato, and F. Succetti, “Metodo di identificazione di utente durante accessi tramite computer, e relativo sistema”, industrial invention patent (IT Italy) n. 102021000016136 of 03 August 2023.