时变时滞随机神经网络的全局均方指数同步

2017 Ninth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2017-02-01 DOI:10.1109/ICACI.2017.7974494

Yinzhe Wu, J. Zhong, Ling Liu

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引用次数: 1

摘要

本文研究了时变时滞随机神经网络的全局均方指数同步问题。两种类型的控制方案被用于同步一类msdn。利用Lyapunov函数和itô公式建立了不同系统结构的各种同步条件。给出了一些统计实例来验证结果。

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Global mean square exponential synchronization of stochastic neural networks with time-varying delays

In this paper, we study the global mean square exponential synchronization of stochastic neural networks with time-varying delays (MSDNN). Two types of control scheme are served to synchronize a sort of MSDNN. A variety of synchronization qualifications depended on system structure are established by the means of Lyapunov function and itô formula. Some statistical examples are supplied to authenticate the results.

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2017 Ninth International Conference on Advanced Computational Intelligence (ICACI)

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