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Convex Optimization for Signal Processing and Communications: From Fundamentals to Applications
时间:2018-10-23 15:30    点击:   所属单位:通信工程学院
讲座名称 Convex Optimization for Signal Processing and Communications: From Fundamentals to Applications
讲座时间 2018-11-02 10:00:00
讲座地点 北校区新科技楼 1012会议室
讲座人 Prof. Chong-Yung Chi
讲座人介绍 Chong-Yung Chi (祁忠勇) received the Ph.D. degree in Electrical Engineering from the University of Southern California, Los Angeles, California, in 1983. From 1983 to 1988, he was with the Jet Propulsion Laboratory, Pasadena, California. He has been a Professor with the Department of Electrical Engineering since 1989 and the Institute of Communications Engineering (ICE) since 1999 (also the Chairman of ICE during 2002-2005), Tsing Hua University, Hsinchu, Taiwan, China.He has published more than 230 technical papers including more than 90 journal papers (mostly in IEEE Trans. Signal Processing), and a new textbook, Convex Optimization for Signal Processing and Communications from Fundamentals to Applications, CRC Press, 2017 (popularly used in an invited intensive short course more than 15 times in major universities in China since 2010). His current research interests include signal processing for wireless communications, convex analysis and optimization for blind source separation, biomedical and hyperspectral image analysis. He has served as Associate editors for 4 IEEE journals, especially IEEE TSP for 9 years. Currently, he is a member of Sensor Array and Multichannel Technical Committee, IEEE Signal Processing Society. Dr. Chi is a senior member of IEEE.
讲座内容
Convex optimization has been recognized as a powerful tool for solving many scientific and engineering problems, including communications (e.g., coordinated transmit beamforming, resource allocation, secret communications, and energy harvesting) and signal processing (e.g., blind source separation, biomedical image analysis, and hyperspectral image analysis). In-depth and efficient learning of the convex optimization theories and tools can equip one with a new degree of freedom and the capability for solving challenging real-world problems. In this tutorial, Part I introduces some mathematical fundamentals of convex optimization. Then, like a guided journey/exploration, Part II presents how some fundamentals introduced in Part I are applied to the cutting-edge research on wireless communications and signal processing problems. The outline for the two parts is as follows:
 
Part I: Fundamentals of Convex Optimization
 
● Convex sets & convex functions
 
● Convex optimization problems & convex approximations
 
● Dual problems & KKT conditions
 
Part II: Cutting Edge Applications
 
● Robust hybrid beamforming for massive MIMO enabled heterogeneous cellular networks
 
● Nonnegative blind source separation: Hyperspectral unmixing and/or Super resolution images
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