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Global Exponential Stability Analysis of a Class of Dynamical Neural Networks

Global Exponential Stability Analysis of a Class of Dynamical Neural Networks
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摘要 The problem of the global exponential stability of a class of Hopfield neural networks is considered. Based on nonnegative matrix theory, a sufficient condition for the existence, uniqueness and global exponential stability of the equilibrium point is presented. And the upper bound for the degree of exponential stability is given. Moreover, a simulation is given to show the effectiveness of the result. The problem of the global exponential stability of a class of Hopfield neural networks is considered. Based on nonnegative matrix theory, a sufficient condition for the existence, uniqueness and global exponential stability of the equilibrium point is presented. And the upper bound for the degree of exponential stability is given. Moreover, a simulation is given to show the effectiveness of the result.
出处 《Journal of Electronic Science and Technology of China》 2009年第2期171-174,共4页 中国电子科技(英文版)
基金 supported by Sichuan Province Foundation for Applied Basic Research and Leaders of Science and Technology under Grant No.05JY029-068-2
关键词 Index Terms-Global exponential stability NEURALNETWORKS nonnegative matrix. Index Terms-Global exponential stability, neuralnetworks, nonnegative matrix.
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