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Stability analysis of BAM neural networks with time-varying delays
作者姓名:ZHANG Huaguang  WANG Zhanshan
作者单位:1. School of Information Science and Engineering, Northeastern University, Shenyang 110004, China; 2. Department of Information Engineering, Shenyang Ligong University, Shenyang 110168, China
基金项目:Supported by National Natural Science Foundation of China (Grant Nos. 60534010, 60572070, 60521003),the Program for Changjiang Scholars and Innovative Research Team in University
摘    要:Some new criteria for the global asymptotic stability of the equilibrium point for the bi-directional associative memory neural networks with time varying delays are presented. The obtained results present the structure of linear matrix inequality which can be solved efficiently. The comparison with some previously reported results in the literature demonstrates that the results in this paper provide one more set of criteria for determining the stability of the bi-directional associative memory neural networks with delays.

关 键 词:bi-directional  associative  memory  (BAM)  neural  networks    time  varying  delays    global  asymptotic  stability    linear  matrix  inequality  (LMI).

Stability analysis of BAM neural networks with time-varying delays
Authors:ZHANG Huaguang  WANG Zhanshan
Institution:1. School of Information Science and Engineering, Northeastern University, Shenyang 110004, China; 2. Department of Information Engineering, Shenyang Ligong University, Shenyang 110168, China
Abstract:Some new criteria for the global asymptotic stability of the equilibrium point for the bi-directional associative memory neural networks with time varying delays are presented. The obtained results present the structure of linear matrix inequality which can be solved efficiently. The comparison with some previously reported results in the literature demonstrates that the results in this paper provide one more set of criteria for determining the stability of the bi-directional associative memory neural networks with delays.
Keywords:bi-directional associative memory (BAM) neural networks  time varying delays  global asymptotic stability  linear matrix inequality (LMI)  
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