Research Expo 2012 (April 12), I will present my previous and on-going work on sparse signal recovery/compressed sensing using sparse Bayesian learning (SBL).
Here is the abstract:
Compressed sensing / sparse signal recovery is a hot field in signal
processing. Numerous algorithms have been proposed and have shown
promising successes in applications. Among these algorithms, sparse
Bayesian learning (SBL) has outstanding performance.
In this presentation I will summarize our lab's recent work on SBL. I will
present four new models that data-adaptively learn and exploit signals'
temporal, spatial, spatiotemporal, and dynamic information. The derived
algorithms from these models have shown the best, or at least top-tier,
performance among existing compressed sensing algorithms in both
computer simulations and practical applications (e.g. telemonitoring,
biomarker selection in gene expression, source localization, earthquake
detection, neuroimaging). Particularly, some of them have:
(1) solved the challenge of non-sparse physiological signals (e.g. fetal ECG contaminated by strong noise, EEG, EMG, etc)
telemonitoring via wireless body-area networks with ultra-low power
consumption, which was not solved before; (this application will show SBL's ability to recover non-sparse signals with little distortion, using simple sparse binary matrices as its sensing matrices)
(2) achieved higher EEG source localization accuracy than other famous
algorithms in more complicated environments (this application will show SBL's excellent ability under strong noise ( 0dB), highly coherent sensing matrix, and frequently changing signals);
(3) broke the record of predicting cognitive outcomes from neuroimaging
measures in Alzheimer's disease in 2011 (showing SBL's ability to deal with highly coherent sensing matrix);
(4) Brain-Computer Interface (solving the speed problem of SBL)
(5) obtained the best accuracy in earthquake detection in some common
Some of these work have been published or submitted to:
IEEE Trans. on Signal Processing,
IEEE Journal of Selected Topics in Signal Processing,
Proceedings of the IEEE,
IEEE Trans. on Biomedical Engineering,
CVPR 2012, and
ICASSP 2010, 2011, 2012.
Also, a US patent is pending.
Welcome to hear my presentation on the recent progress on various spatiotemporal SBL models!
Photo: N. talangensis (taken by April 7)