2011 Poster Sessions : On Asymptotically Optimal Source Coding and Simulation

Student Name : Mark Mao
Advisor : Robert M. Gray
Research Areas: Information Systems
Abstract:
Four necessary conditions for asymptotically optimal sliding-block or stationary codes for source coding and rate-constrained simulation of IID sources and autoregressive sources are derived. A new coding design algorithm which ensures the satisfaction of all four necessary conditions is presented. The code structure has intuitive similarities to classic random coding arguments as well as to "fake process" methods and alphabet-constrained methods. Experimental results show that the new coding design algorithm provides comparable or superior performance in comparison with previously published methods on common examples, often by significant margins. And in many cases, the performance approaches the theoretical Shannon limit.

Bio:
Mark Zhenyu Mao was born in Beijing, China, in 1974. He received the B.S. degree from Tsinghua University in 1994, the M.S. degree from Kansas State University in 1996, both in Computer Science. He is currently a
Ph.D. student in the Department of Electrical Engineering in Stanford University and is expected to graduate in Summer 2011. His research interests include information theory, source coding, machine learning, and speech recognition.