Main Papers

lick here to see my Google-Scholar Information and all papers


2017

A Robust Random Forest-based Approach for Heart Rate Monitoring Using Photoplethysmography Signal Contaminated by Intense Motion Artifacts
Yalan Ye, Wenwen He, Yunfei Cheng, Wenxia Huang, Zhilin Zhang*
Sensors, 2017 (accepted)
[PDF]

2016

Combining Nonlinear Adaptive Filtering and Signal Decomposition for Motion Artifact Removal in Wearable Photoplethysmography
Yalan Ye, Yunfei Cheng, Wenwen He, Mengshu Hou, Zhilin Zhang*
IEEE Sensors Journal, vol. 16, no. 19, pp. 7133 - 7141, Oct. 2016
[PDF]

Quantized Compressive Sensing for Low-Power Data Compression and Wireless Telemonitoring
Benyuan Liu, Zhilin Zhang
IEEE Sensors Journal, vol. 16, no. 23, pp. 8206-8213, Dec. 2016
[PDF]

The Distortion of Data Compression via Compressed Sensing in EEG telemonitoring for the Epileptic
Benyuan Liu, Zhilin Zhang
BIOCAS 2016

A New Approach for Heart Rate Monitoring using Photoplethysmography Signals Contaminated by Motion Artifacts
Biao Sun, Hui Feng, Zhilin Zhang*
ICASSP 2016


2015

Photoplethysmography-Based Heart Rate Monitoring in Physical Activities via Joint Sparse Spectrum Reconstruction
Zhilin Zhang
IEEE Trans. on Biomedical Engineering, vol. 62, no. 8, pp. 1902 - 1910, August 2015 
[PDF] [Results1] [Results2]
[A multiple measurement vector model in sparse signal recovery was used to jointly estimate spectra of simultaneous PPG and acceleration signals, overcoming some drawbacks in TROIKA. It is simpler, and works well at much lower sampling rate.]

TROIKA: A General Framework for Heart Rate Monitoring Using Wrist-Type Photoplethysmographic Signals During Intensive Physical Exercise
Zhilin Zhang, Zhouyue Pi, Benyuan Liu
IEEE Trans. on Biomedical Engineering, vol. 62, no. 2, pp. 522-531, February 2015
[Proposed a framework called TROIKA, revealed three essentials in estimating heart rate during intensive physical exercise, namely signal decomposition, high-resolution spectrum estimation, and spectral peak tracking with verification. ]


Photoplethysmography-Based Heart Rate Monitoring Using Asymmetric Least Squares Spectrum Subtraction and Bayesian Decision Theory
Biao Sun, Zhilin Zhang*
IEEE Sensors Journal, vol. 15, no. 12, pp. 7161-7168, 2015
[PDF]

Combining Combining Ensemble Empirical Mode Decomposition with Spectrum Subtraction Technique for Heart Rate Monitoring Using Wrist-Type Photoplethysmography
Yangsong Zhang, Benyuan Liu, Zhilin Zhang*
Biomedical Signal Processing and Control, vol. 21, pp. 119-125, 2015
[PDF]

Undergraduate Students Compete in the IEEE Signal Processing Cup: Part 3
Zhilin Zhang
IEEE Signal Processing Magazine, vol. 32, no. 6, 2015
[PDF]

Undergraduate Students Compete in the IEEE Signal Processing Cup: Part 1
Kin-Man Lam, Carlos Oscar S. Sorzano, Zhilin Zhang, Patrizio Campisi
IEEE Signal Processing Magazine, vol. 32, no. 4, pp. 123-125, July 2015

Mitigation of Phase Noise and Phase Rotation in Single-Carrier Communication Systems Using Pilots and Smoothing Technique
Zhilin Zhang, Steven Loh, Shadi Abu-Surra, Rakesh Taori
IEEE International Conference on Ubiquitous Wireless Broadband, Oct. 4-7, 2015
[PDF]


2014

Spatiotemporal Sparse Bayesian Learning with Applications to Compressed Sensing of Multichannel Physiological Signals
Zhilin Zhang, Tzyy-Ping Jung, Scott Makeig, Zhouyue Pi, Bhaskar D. Rao
IEEE Trans. on Neural Systems and Rehabilitation Engineering, vol. 22, no. 6, pp. 1186-1197, 2014
[Proposed a spatio-temporal SBL algorithm. When used in compressed sensing of biosignals, it exploits both inter-channel correlation and temporal correlation of channel signals. In BCI experiments and EEG-based driver's drowsiness estimation, it can compress raw EEG data by more than 80% without deteriorating performance.]

Identifying the Neuroanatomical Basis of Cognitive Impairment in Alzheimer's Disease by Correlation- and Nonlinearity-Aware Sparse Bayesian Learning
Jing Wan*, Zhilin Zhang*, Bhaskar D. Rao, Shiaofen Fang, Jingwen Yan, Andrew Saykin, Li Shen. (*equal contribution)
IEEE Trans. on Medical Imaging, vol. 33, no. 7, pp. 1475-1487, 2014
[Based on a sparse multivariate regression model, proposed a sparse Bayesian learning algorithm to identify sparse imaging features by exploiting inter-vector correlation and intra-vector correlation in the regression coefficient matrix, and exploiting the nonlinear relationship between the response and the predictors.]

Heart Rate Monitoring from Wrist-Type Photoplethysmographic (PPG) Signals During Intensive Physical Exercise
Zhilin Zhang
The 2nd IEEE Global Conference on Signal and Information Processing (GlobalSIP 2014), Dec.3-5, 2014
[PDF]
[An early version of the TROIKA algorithm; See the full journal paper in IEEE T-BME]

Training-Free Non-Intrusive Load Monitoring of Electric Vehicle Charging with Low Sampling Rate
Zhilin Zhang, Jae Hyun Son, Ying Li, Mark Trayer, Zhouyue Pi, Dong Yoon Hwang, Joong Ki Moon
The 40th Annual Conference of the IEEE Industrial Electronics Society (IECON 2014), Oct.29-Nov.1, 2014
[PDF[Matlab Code]
[Proposed a training-free algorithm for energy disaggregation of electric vehicle (EV) battery charging load from real power aggregated signals sampled at 1/60 Hz. High performance was verified on real-world data recorded from 11 houses over 1+ year.]

Energy-Efficient Telemonitoring of Physiological Signals via Compressed Sensing: A Fast Algorithm and Power Consumption Evaluation
Benyuan Liu, Zhilin Zhang, Gary Xu, Hongqi Fan, Qiang Fu
Biomedical Signal Processing and Control, vol.11, pp.80-88, 2014
[Using an FPGA prototype, showed BSBL as the encoder can save more energy/power and other on-chip computing resources than a low-power wavelet compression algorithm]

EEG Complexity Modifications and Altered Compressibility in Mild Cognitive Impairment and Alzheimer's Disease
D. Labate, F. La Foresta, I. Palamara, G. Morabito, A.Bramanti, Z. Zhang, F.C. Morabito
Recent Advances of Neural Network Models and Applications, vol. 26, 2014, pp.163-173
[PDF]
[Using BSBL-BO to extract EEG features for classifying Alzheimer's Disease]



2013

Extension of SBL Algorithms for the Recovery of Block Sparse Signals with Intra-Block Correlation
Zhilin Zhang, Bhaskar D. Rao
IEEE Trans. on Signal Processing, vol. 61, no. 8, pp. 2009-2015, 2013 
[PDF] [Matlab Code] [Web Page
[The first paper studied effects of intra-block correlation in block-sparse model; proposed the block sparse Bayesian learning (BSBL) framework.]

Compressed Sensing for Energy-Efficient Wireless Telemonitoring of Noninvasive Fetal ECG via Block Sparse Bayesian Learning
Zhilin Zhang, Tzyy-Ping Jung, Scott Makeig, Bhaskar D. Rao
IEEE Trans. on Biomedical Engineering,  vol. 60, no. 2, pp. 300-309, 2013 
[PDF] [Matlab Code] [Web Page]
[Used BSBL to reconstruct raw fetal ECG. Showed BSBL can directly recover non-sparse correlated signals without using any dictionary matrix. Maybe the first solid evidence showing that exploiting correlation is an effective way to reconstruct non-sparse signals in any domains.]

Compressed Sensing of EEG for Wireless Telemonitoring with Low Energy Consumption and Inexpensive Hardware
Zhilin Zhang, Tzyy-Ping Jung, Scott Makeig, Bhaskar D. Rao
IEEE Trans. on Biomedical Engineeringvol. 60, no. 1, pp. 221-224, 2013 (Special Issue on Health Informatics and Personalized Medicine, Acceptance Rate: 23/210 = 10.9%)
[Applied BSBL to wireless telemonitoring of EEG, showing DCT coefficients can be recovered using block-structure model]

Compressed Sensing for Energy-Efficient Wireless Telemonitoring: Challenges and Opportunities (invited paper)
Zhilin Zhang, Bhaskar D. Rao, Tzyy-Ping Jung
Asilomar Conference on Signals, Systems, and Computers (Asilomar 2013), California, Nov. 2013 
[PDF]
[Discussed the non-sparsity challenge in compressed sensing of biosignals for wireless telemonitoring; proposed the spatio-temporal SBL algorithm (ST-SBL)]

Compression via Compressive Sensing: A Low-Power Framework for the Telemonitoring of Multi-Channel Physiological Signals
Benyuan Liu, Zhilin Zhang, Hongqi Fan, Qiang Fu
2013 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Shanghai, Dec. 2013, pp.9 - 12

Robust Face Recognition via Block Sparse Bayesian Learning
Taiyong Li, Zhilin Zhang
Mathematical Problems in Engineering, Volume 2013 (2013), Article ID 695976
[PDF]



2012

Sparse Signal Recovery Exploiting Spatio-Temporal Correlation
Zhilin Zhang
Ph.D. Dissertation, University of California at San Diego, 2012
[PDF]

Evolving Signal Processing for Brain-Computer Interface  (invited review) 
Scott Makeig, Christian Kothe, Tim Mullen, Nima Bigdely-Shamlo, Zhilin Zhang, Kenneth Kreutz-Delgado
Proceedings of the IEEE, vol. 100, Special Centennial Issue, pp. 1567-1584, May 2012  
[PDF]
[Discuss the challenges and technical problems associated with building robust and useful BCI models]

Recovery of Block Sparse Signals Using the Framework of Block Sparse Bayesian Learning 
Zhilin Zhang, Bhaskar D. Rao 
ICASSP 2012 
[PDF] [Supplementary] [Matlab Code] [Web Page] [Slides
[Studied the recovery of block sparse signals and extended conventional approaches in two directions; one is learning and exploiting intra-block correlation, and the other is generalizing signals' block structure such that the block partition is not needed to be known for recovery. The journal version can be found here]

Sparse Bayesian Multi-Task Learning for Predicting Cognitive Outcomes from Neuroimaging Measures in Alzheimer's Disease 
Jing Wan*, Zhilin Zhang*, Jingwen Yan, Taiyong Li, Bhaskar D. Rao, Shiaofen Fang, Sungeun Kim, Shannon Risacher, Andrew Saykin, Li Shen  (*equal contribution) 
IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2012), pp.940--947, Jun.16-21, 2012
[PDF] [Code (available soon)] 
[Proposed a much fast variant of T-MSBL for multi-task learning; Connected it to many well-established algorithms including group Lasso, mixed L2-L1 based algorithms, etc; Achieved the highest prediction accuracy]

Sparse Signal Recovery in the Presence of Intra-Vector and Inter-Vector Correlation (invited paper) 
Bhaskar D. Rao, Zhilin Zhang, Yuzhe Jin
2012 International Conference on Signal Processing and Communications (SPCOM 2012), India, July 2012
[PDF]
[A short review paper on the problem of sparse signal recovery when there is correlation among the values of non-zero entries of solution vectors/matrices.]

From Sparsity to Structured Sparsity: Bayesian Approach (invited paper) 
Hong Sun, Zhilin Zhang, Lei Yu
Signal Processing (Chinese), vol. 28, no. 6, pp. 759-773, 2012
[PDF]
[Review on sparse Bayesian learning]


2011

Sparse Signal Recovery with Temporally Correlated Source Vectors Using Sparse Bayesian Learning
Zhilin Zhang, Bhaskar D. Rao
IEEE Journal of Selected Topics in Signal Processing, vol.5, no. 5, pp. 912-926, 2011 
[PDF(corrected)] [Matlab Code] [Web Page
[The first work that systematically studies temporal correlation (or inter-vector correlation) in the MMV model. Proposed the T-MSBL/T-SBL algorithms.]

Iterative Reweighted Algorithms for Sparse Signal Recovery with Temporally Correlated Source Vectors 
Zhilin Zhang, Bhaskar D. Rao 
ICASSP 2011
[PDF] [Matlab Code
[By connecting the T-SBL/T-MSBL to iterative reweighted L2 algorithms, the paper proposes an effective strategy to improve most existing iterative reweighted L2 algorithms for the MMV model. As an example, a temporal extension of M-FOCUSS is derived.]

Exploiting Correlation in Sparse Signal Recovery Problems: Multiple Measurement Vectors, Block Sparsity, and Time-Varying Sparsity 
Zhilin Zhang, Bhaskar D. Rao 
ICML 2011 Workshop on Structured Sparsity: Learning and Inference, July, 2011 
[PDF] [Code
[Described three sparse models via SBL; suggested using MMV models to approximate time-varying sparsity model]


2010

[4] Sparse Signal Recovery in the Presence of Correlated Multiple Measurement Vectors 
Zhilin Zhang, Bhaskar D. Rao 
ICASSP 2010
[PDF] [Matlab Code
[The first paper to exploit the temporal correlation in the MMV model; The AR-SBL algorithm is proposed.]


Before 2010

Morphologically Constrained ICA for Extracting Weak Temporally Correlated Signals
Zhi-Lin Zhang
Neurocomputing 71(7-9) (2008) 1669-1679
[PDF] [Matlab Code]
[Gave detailed analysis on constrained ICA framework; Proposed a hybrid algorithm for extracting weak sources with temporal structures; The Algorithm can extract sources with the same period]

Linear Prediction Based Blind Source Extraction Algorithms in Practical Applications 
Zhi-Lin Zhang, Liqing Zhang 
ICA 2007
[PDF] [Color Version
[Points out that most linear-prediction based BSE algorithms have two crucial problems, i.e, the MCA nature and the switch phenomenon]

Robust Extraction of Specific Signals with Temporal Structure
Zhi-Lin Zhang, Zhang Yi
Neurocomputing, vol. 69, no.7-9, pp.888-893, 2006 
[PDF] [Matlab Code]
[Proposed a BSE algorithm for extracting sources with temporal structures via maximizing autocorrelation at multiple lags.]

Extraction of Temporally Correlated Sources with Its Application to Non-invasive Fetal Electrocardiogram Extraction
Zhi-Lin Zhang, Zhang Yi
Neurocomputing, vol. 69, no.7-9, pp.900-904, 2006 
[PDF
[Proposed a BSE algorithm jointly exploiting temporal correlation structures and higher-order statistics of desired sources.]

Extraction of a Source Signal Whose Kurtosis Value Lies in a Specific Range
Zhi-Lin Zhang, Zhang Yi
Neurocomputing, vol. 69, no.7-9, pp.894-899, 2006
[PDF
[Proposed a BSE algorithm with a prior knowledge on the kurtosis range of desired sources.]

A Two-stage Based Approach for Extracting Periodic Signals 
Zhi-Lin Zhang, Liqing Zhang 
ICA 2006
[PDF] [Matlab Code]
[New BSE algorithm to extract periodic or quasi-periodic signals]

Two-Stage Temporally Correlated Source Extraction Algorithm with Its Application in Extraction of Event-Related Potentials 

Zhi-Lin Zhang, Liqing Zhang, Xiu-Ling Wu, Jie Li, Qibin Zhao 
ICONIP 2006 
[PDF



ċ
CORNLIN.m
(16k)
Zhilin Zhang,
Oct 15, 2015, 1:03 AM
ċ
Compressed Sensing of EEG_v2.zip
(273k)
Zhilin Zhang,
Apr 12, 2013, 10:24 PM
ą
Zhilin Zhang,
Jan 6, 2016, 7:32 AM
ą
Zhilin Zhang,
Jan 6, 2016, 7:32 AM
ą
Zhilin Zhang,
Jan 7, 2017, 12:11 PM
ċ
JOSS12.zip
(19k)
Zhilin Zhang,
Sep 28, 2015, 8:09 PM
ċ
JOSS_TEST10.zip
(13k)
Zhilin Zhang,
Sep 28, 2015, 8:09 PM
Ċ
Zhilin Zhang,
Jan 8, 2015, 10:24 PM
Ċ
Zhilin Zhang,
Aug 17, 2015, 12:01 AM
ċ
STSBL_DEMO.zip
(1623k)
Zhilin Zhang,
Oct 15, 2015, 12:53 AM
ċ
TROIKA12.zip
(20k)
Zhilin Zhang,
Sep 28, 2015, 8:08 PM
ċ
TROIKA_TEST10.zip
(14k)
Zhilin Zhang,
Nov 14, 2015, 10:15 AM
Ċ
Zhilin Zhang,
Apr 12, 2012, 3:56 PM
Ċ
Zhilin Zhang,
Apr 12, 2012, 3:57 PM
Comments