Synchronization of Stochastic Memristive Neural Networks with Retarded and Advanced Argument

R. Xian
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引用次数: 2

Abstract

In this paper, we discuss the driving-response synchronization problem for two memristive neural networks with retarded and advanced arguments under the condition of additional noise. The control law is related to the linear time-delay feedback term, and the discontinuous feedback term. Moreover, the random different equation is used to prove the stability of this theory. At the end, the simulation results verify the correctness of the theoretical results.
迟滞超前参数随机记忆神经网络的同步
本文讨论了在附加噪声条件下,具有滞后参数和超前参数的两个记忆神经网络的驱动-响应同步问题。控制律与线性时滞反馈项和不连续反馈项有关。并利用随机差分方程证明了该理论的稳定性。最后,仿真结果验证了理论结果的正确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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