Rice University

Events at Rice


Electrical and Computer Engineering
Dean of Engineering
Faculty Host: Rich Baraniuk

Speaker: Yoram Bresler

ECE Seminar Series: Blind Signal Processing: Sparse Signal Reconstruction in Bilinear Inverse Problems (698/699)

Wednesday, April 5, 2017
4:00 PM  to 5:00 PM

1064  Duncan Hall
Rice University
6100 Main St
Houston, Texas, USA

While the solution of linear inverse problems (BIPs) under both classical signal models and modern sparsity models has been studied extensively and is well understood, relatively little has been known about the solution of bilinear inverse problems. In signal processing, these problems arise in so-called blind signal recovery applications. One notable example is blind deconvolution, with applications in blind image deblurring, blind channel equalization, speech dereverberation, and seismic data analysis. Another important example, is blind gain and phase calibration, which arises in many applications, including inverse rendering in computational relighting (albedo estimation with unknown lighting), blind phase and gain calibration in sensor array processing, and multichannel blind deconvolution. Without further constraints, these bilinear inverse problems do not admit a unique solution. Nonetheless, in practice, subspace or sparsity constraints have been imposed to reduce the search space, and have shown some empirical success. However, until recently, existing theoretical analysis on uniqueness in these problems was rather limited. We describe a framework for identifiability in bi-linear inverse problems, and present the first algebraic results on sample complexity that guarantee recovery under minimal requirements. We also propose a practical recovery algorithm for blind deconvolution that achieves guaranteed optimal scaling of the sample complexity up to logarithmic factors, both in theory and in numerical experiments.

Biography of Yoram Bresler:
Yoram Bresler received the B.Sc. (cum laude) and M.Sc. degrees from the Technion, Israel Institute of Technology, and the Ph.D de¬gree from Stanford University, all in Electrical Engineering. In 1987 he joined the University of Illinois at Urbana-Champaign, where he is currently the GEBI Founder Professor of Engineering at the Departments of Electrical and Computer Engineering and Bioengineering, and at the Co¬ordinated Science Laboratory. He is also President and Chief Technology O?cer at In¬staRecon, Inc., a startup he co-founded to commercialize breakthrough technology for tomographic reconstruction developed in his academic research. His current research in¬terests include statistical signal processing and machine learning for signal processing, and their applications to inverse problems in imaging, and in particular compressed sensing, computed tomography, and MRI. Dr. Bresler has served on the editorial board of several journals, including the IEEE Transactions on Signal Processing, the IEEE Journal on Selected Topics in Signal Processing, Machine Vision and Applications, and the SIAM Journal on Imaging Science, and on various committees of the IEEE. Dr. Bresler is a fellow of the IEEE and of the AIMBE. He received two Best Journal Paper Awards from the IEEE Signal Processing society, and two papers he coauthored with his students received the Young Author Best Journal Paper Award from the same society, in 2001 and 2016, respectively. He is the recipient of a 1991 NSF Presidential Young Investigator Award, the Technion (Israel Inst. of Technology) Fellowship in 1995, and the Xerox Senior Award for Faculty Research in 1998. He was named a University of Illinois Scholar in 1999, appointed as an Associate at the Center for Advanced Study of the University in 2001-2, and Faculty Fellow at the National Cener for Supercomputing Ap¬plications (NCSA) in 2006. In 2016 he was appointed an IEEE Signal Processing Society Distinguished Lecturer.

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