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Mode and Delay-Dependent Adaptive Exponential Synchronization in th Moment for Stochastic Delayed Neural Networks With Markovian Switching

机译:马尔可夫切换的随机时滞神经网络的矩模和时变相关自适应指数同步

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摘要

In this brief, the analysis problem of the mode and delay-dependent adaptive exponential synchronization in $p$th moment is considered for stochastic delayed neural networks with Markovian switching. By utilizing a new nonnegative function and the $M$-matrix approach, several sufficient conditions to ensure the mode and delay-dependent adaptive exponential synchronization in $p$th moment for stochastic delayed neural networks are derived. Via the adaptive feedback control techniques, some suitable parameters update laws are found. To illustrate the effectiveness of the $M$ -matrix-based synchronization conditions derived in this brief, a numerical example is provided finally.
机译:在本文中,对于具有马尔可夫切换的随机延迟神经网络,考虑了$ p $ th矩中与模式和​​延迟相关的自适应指数同步的分析问题。通过使用新的非负函数和$ M $-矩阵方法,导出了几个足以确保随机延迟神经网络在$ p $矩中依赖于模式和依赖于延迟的自适应指数同步的条件。通过自适应反馈控制技术,找到了一些合适的参数更新定律。为了说明此摘要中基于$ M $-基于矩阵的同步条件的有效性,最后提供了一个数值示例。

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