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INFLUENCE OF NOISE AND DELAY ON REACTION-DIFFUSION RECURRENT NEURAL NETWORKS

INFLUENCE OF NOISE AND DELAY ON REACTION-DIFFUSION RECURRENT NEURAL NETWORKS
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摘要 In this paper, the influence of the noise and delay upon the stability property of reaction-diffusion recurrent neural networks （RNNs） with the time-varying delay is discussed. The new and easily verifiable conditions to guarantee the mean value exponential stability of an equilibrium solution are derived. The rate of exponential convergence can be estimated by means of a simple computation based on these criteria. In this paper, the influence of the noise and delay upon the stability property of reaction-diffusion recurrent neural networks （RNNs） with the time-varying delay is discussed. The new and easily verifiable conditions to guarantee the mean value exponential stability of an equilibrium solution are derived. The rate of exponential convergence can be estimated by means of a simple computation based on these criteria.
作者 Li Wu
机构地区 Nanjing Institute of Technology
出处 《Analysis in Theory and Applications》 2006年第3期283-300,共18页 分析理论与应用（英文刊）
关键词 Recurrent neural networks REACTION-DIFFUSION variable delay white noise mean valueexponential stability method of variation parameter M-matrix properties stochastic analysis Recurrent neural networks, reaction-diffusion, variable delay, white noise, mean valueexponential stability, method of variation parameter, M-matrix properties, stochastic analysis
分类号 O17 [理学—基础数学]
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参考文献14

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二级参考文献6

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共引文献20

Analysis in Theory and Applications
2006年 第3期

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