papers

Articles in Journals and Chapters of Books:

  1. P.M. Lima: "Numerical Investigation of Stochastic Neural Field Equations", in Advances in Mathematical Methods and High Performance Computing: V.K. Sing , D. Gao, A. Fischer, Eds., Springer, 2019, pp. 51-67. https://link.springer.com/chapter/10.1007/978-3-030-02487-1_2

  2. G.Yu. Kulikov, P.M. Lima and M.V. Kulikova. Numerical solution of the neural field equation in the presence of random disturbance, Journal of Computational and Applied Mathematics (2019), https://doi.org/10.1016/j.cam.2019.112563.

  3. D. Avitabile, S. Coombes, P.M. Lima, Numerical Investigation of a Neural Field Model Including Dendritic Processing, Journal of Computational Dynamics, V.7 (2020), pp. 271-290.https://www.aimsciences.org/article/doi/10.3934/jcd.2020011

  4. F: Ferreira, W. Wojtak, E. Sousa, L. Louro, E. Bicho and W. Erlhagen, "Rapid learning of complex sequences with time constraints: A dynamic neural field model", IEEE Transactions on Cognitive and Developmental Systems (2020) https://ieeexplore.ieee.org/document/9085956

  5. W. Wojtak, F. Ferreira, P. Vicente, E. Bicho and W. Erlhagen, "A neural integrator model for planning and value-based decision making of a service robot" ,Neural Computing and Applications (2020): 1-20. doi.org/10.1007/s00521-020-05224-8

  6. W. Wojtak, S. Coombes, D. Avitabile, E. Bicho, W.Erlhagen, A dynamic neural field model of continuous input integration, Byological Cybernetics (2021), https://link.springer.com/article/10.1007/s00422-021-00893-7.

  7. M.V.Kulikova, P.M. Lima, .G.Yu. Kulikov, Sequential method for fast neural population activity reconstruction in the cortex from incomplete noisy measurements, Computers in Biology and Medicine , 141 (2022) 105103. https://www.sciencedirect.com/science/article/abs/pii/S0010482521008970

  8. P.M. Lima, W. Erlhagen, M.V. Kulikova, G. Yu. Kulikov, Numerical solution of the stochastic neural field rquation with applications to working memory, Physica A,: Statistical Mechanics and its Applications, 596 (2022), 127166. https://doi.org/10.1016/j.physa.2022.127166.

  9. T. Sequeira, P.M. Lima, Numerical simulations of one- and two-dimensional stochastic neural field equations with delay, Journal of Computational Neurosciences, 50 (2022) 299- 311, https://doi.org/10.1007/s10827-022-00816-w .

  10. G.Yu. Kulikov, M.V. Kulikova, Accuracy analysis of numerical simulations and noisy data assimilations in two-dimensional stochastic neural fields with infinite signal transmission speed, in preparation.

  11. M.V.Kulikova, P.M. Lima, G.Yu. Kulikov, Data-driven state restoration and parameter adaptation in stochastic neural fields with finite signal transmission rate, in preparation.

  12. W. Wojtak, S. Coombes, D. Avitabile, E. Bicho, W.Erlhagen, Analysis of two-dimensional bump solutions in a neural integrator model, in preparation.

  13. F. Ferreira, W. Wojtak, , E. Bicho and W. Erlhagen, Adaptive timing in a dynamic neural field architecture for human-robot collaboration, in preparation

  14. F. Ferreira, W. Wojtak, P. Guimarães, P. Barbosa, S. Monteiro, E. Bicho, and W. Erlhagen, A dynamic neural field approach to intelligent cockpits: Learning driver routines in space and time", in preparation



Articles in Conference Proceedings:

1. G.Yu. Kulikov, M.V. Kulikova and P.M. Lima. "Numerical Simulation of Neural Fields with Finite Transmission Speed and Random Disturbance". Proceedings of the 23rd International Conference on System Theory, Control and Computing, Sinaia, Romania, 2019, pp. 644-649. https://ieeexplore.ieee.org/abstract/document/8885972


2. M.V. Kulikova, G.Yu. Kulikov and P.M. Lima. Effective Numerical Solution to Two-Dimensional Stochastic Neural Field Equations. Proceedings of the 23rd International Conference on System Theory, Control and Computing, Sinaia, Romania, ICSTCC 2019, 2019, pp. 650-655. https://ieeexplore.ieee.org/abstract/document/8885614

3. W. Wojtak, F. Ferreira, E. Bicho and W. Erlhagen , "Neural field model for measuring and reproducing time intervals", Proceedings of the 28th International Conference on Artificial Neural Networks (ICANN 2019), I. V. Tetko et al. (Eds.), LNCS 11727,Springer, 2019 , pp. 327–338. https://www.researchgate.net/publication/335699180

4. W. Wojtak, F. Ferreira, E. Bicho and W. Erlhagen ," Numerical analysis of the shape of bump solutions in a neuronal model of working memory", 16th International Conference of Numerical Analysis and Applied Mathematics (ICNAAM 2018), AIP Conference Proceedings, 2116, pp. 250003 (2019) https://www.researchgate.net/publication/327645098_Numerical_analysis_of_the_shape_of_bump_solutions_in_a_neuronal_model_of_working_memory

5. F. Ferreira, W. Wojtak, W. Erlhagen, P. Vicente, A. Patel, S. Monteiro and Estela Bicho (2019), " A dynamic neural model for endowing intelligent cars with the ability to learn driver routines: where to go, when to arrive and how long to stay there?", Cognitive Vehicles Workshop - IROS 2019, Macau, China, 2019, pp.15-18 (best Poster Award) https://cogvehicles2019.github.io/assets/proceedings/proceedings.pdf

6. A, Cunha, F. Ferreira, W. Erlhagen, E. Sousa, L Louro, P. Vicente,S. Monteiro and E. Bicho. Towards Collaborative Robots as Intelligent Co-workers in Human Robot Joint Tasks: what to do and who does it? Proceedings of 52nd International Symposium on Robotics - ISR 2020, Munich, Germany, p 1-8 (2020).

doi.org/10.1007/978-3-030-35990-4_30

7. P. M. Lima and W. Erlhagen, Applications of Neural Field Equations to Working Memory, Proceedings of the VII International Conference on Mathematics, its Applications and Mathematical Education, September 8 -12, 2020, Ulan-Ude , Russian Federation. http://www.math.tecnico.ulisboa.pt/~plima/papers/paperMAME.pdf

8. A, Cunha, F. Ferreira, W. Erlhagen, E. Sousa, L Louro, P. Vicente,S. Monteiro and E. Bicho. Towards Collaborative Robots as Intelligent Co-workers in Human Robot Joint Tasks: what to do and who does it? Proceedings of 52nd International Symposium on Robotics - ISR 2020, Munich, Germany, p 1-8 (2020).

https://ieeexplore.ieee.org/abstract/document/9307464

9. M.V. Kulikova, G.Yu. Kulikov and P.M. Lima. Accuracy Study in Numerical Simulations to Stochastic Neural Field Equations, 24th International Conference on System Theory, Control and Computing Joint Conference SINTES 24, SACCS 20, SIMSIS 24, CONTI 13. 8 - 10 October 2020, Sinaia, Romania.

DOI: 10.1109/ICSTCC50638.2020.9259762

10. P.M. Lima, W. Erlhagen, M.V. Kulikova, G. Yu. Kulikov, Mathematical Modeling of Working Memory in the Presence of Random Disturbance using Neural Field Equations, Proceedings of MNPS, EPJ Web of Conferences, 248,01021 (2021). https://doi.org/10.1051/epjconf/202124801021

11. Wojtak, W., Ferreira, F., Guimarães, P., Barbosa, P., Monteiro, S., Erlhagen, W., and Bicho, E. Towards endowing intelligent cars with the ability to learn the routines of multiple drivers: A dynamic neural field model. In Proceedings of the International Conference on Computational Science and Its Applications, LNCS, volume 12952, pages 337–349. Springer (2021). https://link.springer.com/chapter/10.1007/978-3-030-86973-1_24

12. Ferreira, F., Wojtak, W., Fernandes, C., Guimarães, P., Monteiro, S., Bicho, E., and Erlhagen, W. Dynamic identification of stop locations from GPS trajectories based on their temporal and spatial characteristics. In Proceedings of the 2021 International Conference on Artificial Neural Networks (ICANN 2021), LNCS, volume 12894, pages 347–359. Springer (2021). https://link.springer.com/chapter/10.1007/978-3-030-86380-7_28

  1. M.V. Kulikova, P.M. Lima, .G.Yu. Kulikov, Reconstruction of hidden states in stochastic neural field equations with infinite signal transmission rate, Proceedings of the 25th Internatonal Conference on System Theory, Control and Computing, p. 358-365 (2021). https://ieeexplore.ieee.org/document/9607081

  1. M.V.Kulikova, P.M. Lima, .G.Yu. Kulikov, Accurate Ito-Taylor-Discretization-Based State Estimation in Stochastic Neural Field Equations with Infinte Signal Transmission Rate,Proceedings of ECC2022 (2022), p. 1436-1441. DOI: 10.23919/ECC55457.2022.9838121

  2. . M.V.Kulikova, P.M. Lima, G.Yu. Kulikov, Pattern Recognition Facilities of Extended Kallman Filtering in Stochastic Neural Fields,Proceedings of ECC2022 (2022), p.1061-1066. DOI: 10.23919/ECC55457.2022.9838068