STUDIES OF THE DYNAMIC BEHAVIORS OF A CLASS OF LEARNING ASSOCIATIVE NEURAL NETWORKS

作     者：曾黄麟 

作者机构：Sichuan Institute of Light Industry & Chemical Technology Zigong 643033 

出 版 物：《Journal of Electronics(China)》 (电子科学学刊（英文版）)

年 卷 期：1994年第11卷第3期

页      面：208-216页

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Associative neural network Learning algorithm Dynamic characteristics Structure exponential stability 

摘      要：This paper investigates exponential stability and trajectory bounds of motions of equilibria of a class of associative neural networks under structural variations as learning a new pattern. Some conditions for the possible maximum estimate of the domain of structural exponential stability are determined. The filtering ability of the associative neural networks contaminated by input noises is analyzed. Employing the obtained results as valuable guidelines, a systematic synthesis procedure for constructing a dynamical associative neural network that stores a given set of vectors as the stable equilibrium points as well as learns new patterns can be developed. Some new concepts defined here are expected to be the instruction for further studies of learning associative neural networks.