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Adaptive Synchronization for Neutral-Type Neural Networks with Stochastic Perturbation and Markovian Switching Parameters

机译:具有随机扰动和马尔可夫切换参数的中立型神经网络的自适应同步

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摘要

In this paper, the problem of adaptive synchronization is investigated for stochastic neural networks of neutral-type with Markovian switching parameters. Using the -matrix approach and the stochastic analysis method, some sufficient conditions are obtained to ensure three kinds of adaptive synchronization for the stochastic neutral-type neural networks. These three kinds of adaptive synchronization include the almost sure asymptotical synchronization, exponential synchronization in th moment and almost sure exponential synchronization. Some numerical examples are provided to illustrate the effectiveness and potential of the proposed design techniques.
机译:本文研究了具有马尔可夫切换参数的中立型随机神经网络的自适应同步问题。使用-matrix方法和随机分析方法,可以获得一些充分的条件,以确保随机中立型神经网络的三种自适应同步。这三种自适应同步包括几乎确定的渐近同步,瞬间的指数同步和几乎确定的指数同步。提供了一些数值示例来说明所提出的设计技术的有效性和潜力。

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