学术报告第201809期

报告题目：Nonlinear Operation Models for Producing 1D Chaotic Maps

报 告 人：周怡聪 副教授（澳门大学）

报告时间：2018年4月8日10：15

报告地点：南一楼中311室

Abstract: Chaos is a particular nonlinear dynamic with clear boundaries and high sensitivity to initial states. Any small variation of initial states eventually results in remarkable end states (known as “butterfly effect”). Because chaotic systems have excellent properties like initial states sensitivity, ergodicity and unpredictability, they are widely used in digital communication, system control and cryptography. In this talk, after reviewing several existing chaotic maps, I will present a series of nonlinear operation models that are general frameworks for producing 1D chaotic maps with robust chaos. They include the Cascade, Modulation, Wheel-switching, Fusion, Sine-transform, and Exponential operation models. Using any chaotic maps as seed maps, each operation model can produce a huge number of new chaotic maps. I will investigate unique properties of each operation model, and then show interesting properties of their combinations. Examples and evaluations are provided to show that new chaotic maps generated by these nonlinear operation models and their combinations have better chaotic performance and more complex properties than corresponding seed maps.

Short Biography: Dr. Yicong Zhou received his B.S. degree from Hunan University, Changsha, China, and his M.S. and Ph.D. degrees from Tufts University, Massachusetts, USA, all in electrical engineering. He is currently an Associate Professor and director of the Vision and Image Processing Laboratory in the Department of Computer and Information Science at University of Macau, Macau, China. His research interests include chaotic systems, multimedia security, pattern recognition, and machine learning. Dr. Zhou serves as an Associate Editor for Neurocomputing, Signal Processing: Image Communication, and the Journal of Visual Communication and Image Representation, and a leading co-chair of IEEE SMC Technical Committee on Cognitive Computing. He is a senior member of IEEE and was a recipient of the third price of Macau Natural Science Award in 2014.