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Stochastic quasi-synchronization for uncertain chaotic delayed neural networks

机译:不确定混沌时滞神经网络的随机准同步

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摘要

The stochastic quasi-synchronization issue for uncertain chaotic delayed neural networks (DNNs) is investigated. Stochastic perturbation and three uncertain elements, including the discontinuous activation functions, mismatched connection weight parameters and unknown connection weight parameters, are considered in the chaotic DNNs. According to the Ito formula and the inequality techniques, the parameters update laws and the control laws are given to realize the synchronization. And a stochastic quasi-synchronization criterion is established. Furthermore, sufficient conditions are proposed for the control of the synchronization error bound by choosing appropriate control laws. Some numerical simulations are presented to demonstrate the effectiveness of the theoretical results.
机译:研究了不确定混沌延迟神经网络(DNN)的随机准同步问题。混沌DNN中考虑了随机扰动和三个不确定因素,包括不连续激活函数,不匹配的连接权重参数和未知的连接权重参数。根据伊藤公式和不等式技术,给出了参数更新律和控制律,以实现同步。并建立了一个随机准同步准则。此外,提出了通过选择适当的控制律来控制同步误差范围的充分条件。一些数值模拟被提出来证明理论结果的有效性。

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