应云顶国际4008服务平台信息与系统科学研究所的邀请，美国密歇根理工大学Tian Zhi教授于12月26日来我校进行学术交流并作学术报告。 
  
        时    间：12月26日下午2:30
        地    点：理科楼122室
        报告题目: Compressive Sensing: Basics and Applications in Signal Processing

        报告摘要:
        Sparsity that characterizes many natural and man-made signals has been exploited over the years in a broad range of statistical inference and signal representation applications, leading to the recent exciting results on compressed sensing for signal reconstruction at sub-Nyquist rates. In this talk, I will start with an overview of the motivation, theory and algorithms of compressive sensing. Then, I will elaborate on several applications in signal processing, such as cyclic feature detection for wideband spectrum sensing and MIMO Radar. In particular, I will present a new framework of compressive sensing that we have developed for random processes, particularly for estimating the second-order statistics of signals. It has been well recognized that second-order statistics contain reliable information for random processes and are rich in useful features. Our new framework allows for accurate estimation of useful statistics from compressive measurements using simple least-squares solutions, even when the random signal of interest is non-sparse. This surprising result is owing to the fact that we directly recover the second-order statistics which has less degrees of freedom than the random signal itself.

        报告人简介: 
        Dr. Zhi Tian is a Professor in the Department of Electrical and Computer Engineering of Michigan Technological University. She is currently on leave to serve as a Program Director in the Division of Electrical, Communications and Cyber Systems at the National Science Foundation (NSF) of USA.  Her research interests lie in digital and wireless communications, wireless sensor networks, and signal processing. She has served as Associate Editor for IEEE Transactions on Wireless Communications and IEEE Transaction on Signal Processing. She received a CAREER award from the US NSF in 2003. She is an IEEE Fellow. 

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