Plenary Lecture

Cerebellar Model Neural Networks and their Applications on Control, Signal Processing, and Image Classification

Professor Chih-Min Lin
Electrical and Communication Engineering College
Yuan Ze University

Abstract: Based on biological prototype of human brain and improved understanding of the functionality of the neurons and the pattern of their interconnections in the brain, a theoretical model used to explain the information-processing characteristics of the cerebellum was developed independently by Marr (1969) and Albus (1971). Cerebellar model neural network (CMNN) or called as cerebellar model articulation controller (CMAC) was first proposed by Albus in 1974. CMNN is a learning structure that imitates the organization and functionality of the cerebellum of the human brain. That model revealed the structure and functionality of the various cells and fibers in the cerebellum. The core of CMNN is an associative memory which has the ability to approach complex nonlinear functions. CMNN takes advantage of the input-redundancy by using distributed storage and can learn nonlinear functions extremely quickly due to the on-line adjustment of its system parameters. CMNN is classified as a non-fully connected perceptron-like associative memory network with overlapping receptive-fields. It has good generalization capability and fast learning property and is suitable for a lot of applications. This speech will introduce several new CMNN-based adaptive learning systems proposed by me; these systems combine the advantages of CMNN identification, adaptive learning, control technique, signal processing and image classification. In these systems, the on-line parameter training methodologies, using the Lyapunov theorem, are proposed to guarantee the stability and convergence of these systems. Moreover, the applications of these systems in nonlinear systems control, biped robot control, signal processing of communication system, and computer-aided diagnosis of breast nodules are demonstrated.

Brief Biography of the Speaker: Prof. Chih-Min Lin is currently a Chair Professor and Dean of Electrical and Communication Engineering College, Yuan Ze University, Taiwan. He also serves as an Associate Editor of IEEE Trans. on Cybernetics; Asian Journal of Control; International Journal of Fuzzy Systems; International Journal of Electrical Engineering; and International Journal of Machine Learning and Cybernetics. He has been the Chair of IEEE Computational Intelligence Society Taipei Chapter, the Chair of IEEE Systems, Man, and Cybernetics Society Taipei Chapter; a Board of Governor of IEEE Taipei Section. He has been awarded as the Distinguished Research Professor from National Science Council in Taiwan, the Distinguished Engineering Professor from China Engineering Society in Taiwan, and the Distinguished Electrical Engineering Professor from Chinese Electrical Engineering Society in Taiwan. He has been invited to give 7 keynote speeches in the international conferences. He is now a Board of Governor of IEEE Systems, Man, and Cybernetics Society. His research interests include fuzzy systems, neural network, cerebellar model neural network, and intelligent control systems. He is an IEEE Fellow and IET Fellow. Till now he has published 132 journal papers and 155 conference papers.