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Global asymptotic stability of cellular neural networks with multiple delays
作者姓名:WANG Zhanshan  ZHANG Huaguang
作者单位:1. Key Laboratory of Process Industry Automation, Northeastern University, Shenyang 110004, China; 2. Department of Information Engineering, Shenyang Ligong University, Shenyang 110168, China
基金项目:中国科学院资助项目;辽宁省自然科学基金
摘    要:Global asymptotic stability (GAS) is discussed for cellular neural networks (CNN) with multiple time delays. Several criteria are proposed to ascertain the uniqueness and global asymptotic stability of the equilibrium point for the CNN with delays. These criteria can eliminate the difference between the neuronal excitatory and inhibitory effects. Two examples are presented to demonstrate the effectiveness of the criteria.

关 键 词:cellular  neural  networks    global  asymptotic  stability    multiple  time  delays.

Global asymptotic stability of cellular neural networks with multiple delays
WANG Zhanshan,ZHANG Huaguang.Global asymptotic stability of cellular neural networks with multiple delays[J].Progress in Natural Science,2006,16(2):163-168.
Authors:WANG Zhanshan  ZHANG Huaguang
Institution:1. Key Laboratory of Process Industry Automation, Northeastern University, Shenyang 110004, China;Department of Information Engineering, Shenyang Ligong University, Shenyang 110168, China
2. Department of Information Engineering, Shenyang Ligong University, Shenyang 110168, China
Abstract:Global asymptotic stability (GAS) is discussed for cellular neural networks (CNN) with multiple time delays. Several criteria are proposed to ascertain the uniqueness and global asymptotic stability of the equilibrium point for the CNN with delays. These criteria can eliminate the difference between the neuronal excitatory and inhibitory effects. Two examples are presented to demonstrate the effectiveness of the criteria.
Keywords:cellular neural networks  global asymptotic stability  multiple time delays
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