Title: A New Direction-of-arrival Estimation Method Based on the Regularized Sparse Variable Projection Optimization

Speaker: Prof. Xiao-Ping Zhang

(Ph.D., P.Eng., M.B.A., SMIEEE. Professor, Director of Communication and Signal Processing Applications Laboratory (CASPAL); Program Director of Graduate Studies, Department of Electrical & Computer Engineering, Ryerson University, Canada)

From: Ryerson University, Canada

Time: 2:00 p.m., Dec. 26, 2012

Place: Conference Room 218 at Dezhao South Building, Institute of Acoustics, Chinese Academy of Sciences

Sponsor:

Communication Acoustics Laboratory of Institute of Acoustics, Chinese Academy of Sciences

Welcome!

 

Abstract of the report:

In this talk, we present a new low computational complexity direction-of-arrival (DOA) estimation method based on the regularized sparse variable projection (SVP) optimization. The new method, namely SVP-lp algorithm, estimates a sparse indicative vector (SIV) that indicates the DOA from each visual source corresponding to DOA sampling space. Unlike existing sparse signal representation (SSR) methods for the DOA estimation, which are based on joint-sparse signal representation (JSSR) to reconstruct signal sources themselves, the new SVP-lp method simplifies the JSSR problem as a single sparse signal representation (SSSR) problem by reconstructing a SIV instead of all signal sources. The SVP function is regularized by $l_p<1$ norm. Then we formulate the SVP optimization as an unconstrained optimization problem, which can be solved iteratively. We prove that the new SVP optimization algorithm satisfies the local convergence property and the convergence rate is linear. The experimental results show that the new method has higher accuracy and much lower complexity compared to existing SSR algorithms and traditional subspace based methods.

CV of Xiao-Ping Zhang:

Xiao-Ping Zhang received the B.S. and Ph.D. degrees from Tsinghua University, in 1992 and 1996, respectively, all in electronic engineering. He holds an MBA in Finance, Economics and Entrepreneurship with Honors from the University of Chicago Booth School of Business.

Since Fall 2000, he has been with the Department of Electrical and Computer Engineering, Ryerson University, where he is now Professor, Director of Communication and Signal Processing Applications Laboratory (CASPAL) and Program Director of Graduate Studies. Prior to joining Ryerson, he was a Senior DSP Engineer at SAM Technology, Inc., at San Francisco, and a consultant at San Francisco Brain Research Institute. He held research and teaching positions at the Communication Research Laboratory, McMaster University, and worked as a postdoctoral fellow at the Beckman Institute, the University of Illinois at Urbana-Champaign, and the University of Texas, San Antonio. His research interests include multimedia communications and signal processing, sensor networks and electronic systems, multimedia content analysis, computational intelligence, and applications in bioinformatics, finance, and marketing. He is a frequent consultant for biotech companies and investment firms. He is cofounder and CEO for EidoSearch, an Ontario based company offering a content-based search and analysis engine for financial data.

Dr. Zhang is a registered Professional Engineer in Ontario, Canada, a Senior Member of IEEE and a member of Beta Gamma Sigma Honor Society.He is the publicity co-chair for ICME'06 and program co-chair for ICIC'05.He is currently an Associate Editor for IEEE Transactions on Signal Processing, IEEE Transactions on Multimedia, IEEE Signal Processing letters and for Journal of Multimedia.