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Lag stochastic synchronization of chaotic mixed time-delayed neural networks with uncertain parameters or perturbations

机译:参数或摄动不确定的混沌混合时滞神经网络的时滞随机同步

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摘要

This paper investigates the problem of lag synchronization for a kind of chaotic neural networks with discrete and distributed delays (mixed delays). The driver system has uncertain parameters and uncertain nonlinear external perturbations, while the response system has channel noises. A simple but all-powerful robust adaptive controller is designed to circumvent the effects of uncertain external perturbations such that the response system synchronize with the driver system. Based on the invariance principle of stochastic differential equations and some suitable Lyapunov functions, several sufficient conditions are developed to solve this problem. Moreover, under certain conditions, parameters of the uncertain master system can be estimated. Numerical simulations are exploited to show the effectiveness of the theoretical results.
机译:本文研究了一类具有离散和分布式延迟(混合延迟)的混沌神经网络的滞后同步问题。驱动器系统具有不确定的参数和不确定的非线性外部扰动,而响应系统具有通道噪声。设计了一个简单但功能强大的鲁棒自适应控制器,以规避不确定的外部干扰的影响,从而使响应系统与驱动器系统同步。基于随机微分方程的不变性原理和一些合适的Lyapunov函数,为解决该问题开发了几个充分的条件。而且,在某些条件下,可以估计不确定的主系统的参数。数值模拟被用来证明理论结果的有效性。

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