由澳门太阳集团官方网址主办的“信通论坛”本次邀请 Ryerson University的Xiao-Ping (Steven) Zhang教授，与我校师生共同交流，具体安排如下，欢迎感兴趣的师生参加。
一、主 题：Foundations in Graph Signal Processing
二、主讲人：Xiao-Ping (Steven) Zhang（Professor, Ryerson University, Canada）
四、地 点：清水河校区科研楼B区 108会议室
Defining a sound shift operator for graph signals, similar to the shift operator in classical signal processing, is a foundation in graph signal processing (GSP), since almost all operations, such as filtering, transformation, prediction, are directly related to the graph shift operator. In this talk, I first introduce the basics and motivations of GSP. Then we define a set of energy-preserving shift operators that satisfy many properties similar to their counterparts in classical signal processing, but are different from the shift operators defined in the literature. We decouple the graph structure represented by eigengraphs and the eigenvalues of the adjacency matrix or the Laplacian matrix. We show that the adjacency matrix of a graph is indeed a linear shift invariant (LSI) graph filter with respect to the defined shift operator. We further define autocorrelation and cross-correlation functions of signals on the graph, enabling us to obtain the solution to the optimal filtering on graphs, i.e., the corresponding Wiener filtering on graphs and the efficient spectra analysis and frequency domain filtering in parallel with those in classical signal processing. This new shift operator based GSP framework enables the signal analysis along a correlation structure defined by a graph shift manifold as opposed to classical signal processing operating on the assumption of the correlation structure with a linear time shift manifold. Several illustrative simulations are presented to validate the performance of the designed optimal LSI filters.
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 and Economics with Honors from the University of Chicago Booth School of Business. He is now Professor and Director of Communication and Signal Processing Applications Laboratory (CASPAL), with the Department of Electrical and Computer Engineering, Ryerson University. He has served as Program Director of Graduate Studies. He is cross-appointed to the Finance Department at the Ted Rogers School of Management at Ryerson University. He has been a Visiting Scientist at Research Laboratory of Electronics (RLE), Massachusetts Institute of Technology. His research interests include statistical signal processing and big data analytics, multimedia content analysis, sensor networks and electronic systems, machine learning/AI, and applications in finance, economics, 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 numerical data search and analysis engine for financial big data .
Dr. Zhang is a registered Professional Engineer in Ontario, Canada, and a member of Beta Gamma Sigma Honor Society. He is the general co-chair for 2021 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP2021). He is the general co-chair for 2017 GlobalSIP Symposium on Signal and Information Processing for Finance and Business, and the general co-chair for 2019 GlobalSIP Symposium on Signal, Information Processing and AI for Finance and Business. He is an elected member of IEEE International Conference on Multimedia and Expo (ICME) steering committee. He is the general chair for MMSP'15. He is the publicity chair for ICME'06 and program chair for 2005 International Conference on Intelligent Computing (ICIC'05) and ICIC'10. He served as guest editor for Multimedia Tools and Applications, and the International Journal of Semantic Computing. He is a tutorial speaker in ACM Multimedia 2011 (ACMMM2011), 2013 IEEE International Symposium on Circuits and Systems (ISCAS2013), 2013 IEEE International Conference on Image Processing (ICIP2013), ICASSP2014, 2017 International Joint Conference on Neural Networks (IJCNN 2017) and ISCAS2019. He is Senior Area Editor for IEEE Transactions on Signal Processing and IEEE Transactions on Image Processing. He served as Associate Editor for IEEE Transactions on Signal Processing, IEEE Transactions on Image Processing, IEEE Transactions on Multimedia, IEEE Transactions on Circuits and Systems for Video Technology, and IEEE Signal Processing Letters. He is elected Vice-Chair for Image, Video, and Multidimensional Signal Processing Technical Committee (IVMSP TC) of IEEE Signal Processing Society. He is selected as an IEEE Signal Processing Society Distinguished Lecturer for the term from January 2020 to December 2021. He received 2020 Sarwan Sahota Ryerson Distinguished Scholar Award – the Ryerson University highest honor for scholarly, research and creative achievements.