EE Systems Seminar

Approximate message passing (AMP) decouples linear inverse problems into iterative additive white Gaussian noise (AWGN) scalar channel denoising problems. The first part of the talk provides a tutorial-style overview of AMP, including advantages, a convenient design methodology, and possible pitfalls. The second part describes how we have designed denoising algorithms that recover signals from AWGN, and applied these denoisers within AMP to reconstruct signals in linear inverse problems. Examples include denoising parametric signals, universal denoising for stationary ergodic signals whose input statistics are unknown, and image denoising. Our favorable numerical results indicate that AMP is a promising tool for solving linear inverse problems.

Bio:

Dror Baron received the B.Sc. (summa cum laude) and M.Sc. degrees from the Technion - Israel Institute of Technology, Haifa, Israel, in 1997and 1999, and the Ph.D. degree from the University of Illinois atUrbana-Champaign in 2003, all in electrical engineering.

From 1997 to 1999, he worked at Witcom Ltd. in modem design. From 1999 to 2003, he was a research assistant at the University of Illinois at Urbana-Champaign, where he was also a Visiting Assistant Professor in 2003. From 2003 to 2006, he was a Postdoctoral Research Associate in the Department of Electrical and Computer Engineering at Rice University, Houston, TX. From 2007 to 2008, he was a quantitative financial analyst with Menta Capital, San Francisco, CA. From 2008 to

2010 he was a visiting scientist in the Department of Electrical Engineering at the Technion. Dr. Baron joined the Department of Electrical and Computer Engineering at North Carolina State University in 2010 as an assistant professor. His research interests include information theory and statistical signal processing.