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首页> 外文期刊>International Journal of Robust and Nonlinear Control >Synchronization of coupled neural networks with random coupling strengths and mixed probabilistic time-varying delays
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Synchronization of coupled neural networks with random coupling strengths and mixed probabilistic time-varying delays

机译:具有随机耦合强度和混合概率时变时滞的耦合神经网络的同步

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摘要

This paper investigates the global asymptotic synchronization in an array of coupled neural networks with random coupling strengths, probabilistic interval time-varying coupling delays as well as unbounded distributed delays (mixed delays). Two important integral inequalities that include the Jensen's inequality as a special case are developed. On the basis of the developed inequalities, the properties of random variables and Lyapunov functional method, several delay-dependent sufficient synchronization criteria are derived for the considered model. The derived synchronization criteria are formulated by linear matrix inequalities (LMIs) and can be easily verified by using MATLAB LMI Toolbox. Some existing results are improved and extended by taking different values of parameters of the obtained results. Numerical simulations are finally given to demonstrate the effectiveness of the theoretical results.
机译:本文研究了具有随机耦合强度,概率间隔时变耦合延迟以及无穷分布延迟(混合延迟)的耦合神经网络阵列中的全局渐近同步。发展了两个重要的积分不等式,其中包括詹森不等式作为特例。基于已发展的不等式,随机变量的性质和Lyapunov函数方法,为所考虑的模型导出了几个依赖于延迟的充分同步准则。导出的同步标准由线性矩阵不等式(LMI)表示,可以使用MATLAB LMI Toolbox轻松进行验证。通过采用获得的结果的不同参数值,可以改善和扩展现有的一些结果。最后进行了数值模拟,以证明理论结果的有效性。

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