講座題目：Introductions to Statistical Signal Processing

時(shí)　　間：2012年6月18，20，22，26，27，29日上午9：00~11:00

地　　點(diǎn)：研究生樓307，307，105，105，307，105

主講人介紹

　　Xiaoming Huo received the B.S. degree in mathematics from the University of Science and Technology, China, in 1993, and the M.S. degree in electrical engineering and the Ph.D. degree in statistics from Stanford University, Stanford, CA, in 1997 and 1999, respectively. Since August 2011, he has been a Professor with the School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta.
　　His research interests include statistics and multiscale methodology. He has made numerous contributions on topics such as sparse representation, wavelets, and statistical problems in detectability. His papers appeared in top journals, and some of them are highly cited.
　　He is a senior member of IEEE since May 2004. He was a Fellow of IPAM in September 2004. He won the Georgia Tech Sigma Xi Young Faculty Award in 2005. His work has led to an interview by Emerging Research Fronts in June 2006 in the field of Mathematics – every two months, one paper is selected.

主要內(nèi)容：

　　An overview of current status of statistical signal processing (SSP) in both
Education and research will be given. I will review some key Fundamental principles that are adopted in SSP. Then I will delve into some specific research directions,
particularly those that I have some experience on:
　　(1) nonlinear models, particularly those that are based on manifolds;
　　(2) sparse representations, numerical strategies, and compressive
sensing;
　　(3) detectability and its application in image processing;
　　(4) extraction of directional features in images.