Almost sure adaptive asymptotically synchronization for neutral-type multi-slave neural networks with Markovian jumping parameters and stochastic perturbation
Almost sure adaptive asymptotically synchronization for neutral-type multi-slave neural networks with Markovian jumping parameters and stochastic perturbation
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DOI：
10.1016/j.neucom.2016.05.069
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发表时间：
2016-11
期刊：
影响因子：
6
通讯作者：
Jun Zhou;Xiangwu Ding;Liuwei Zhou;Wuneng Zhou;Jun Yang;Dongbing Tong
中科院分区：
文献类型：
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作者：
Jun Zhou;Xiangwu Ding;Liuwei Zhou;Wuneng Zhou;Jun Yang;Dongbing Tong
研究了具有马尔可夫跳变参数和随机噪声的时滞中立型多从神经网络的自适应同步问题。提出了一个驱动系统和多个响应系统的自适应同步模型。利用广义Ito公式和M矩阵方法，得到了误差控制系统稳定的充分条件，并设计了反馈控制器的更新律，使每个从系统都能与主系统同步。最后通过一个数值例子说明了本文方法和所得结果的有效性。
In this paper, the problem of adaptive synchronization for time-delay neutral-type multi-slave neural networks with Markovian jumping parameters and stochastic noise is researched. The adaptive synchronization model which contains a drive system and multiple response systems is presented. By using of the generalized It o^’s formula and the M-matrix method, the sufficient condition is obtained to guarantee that the error control system is stable, and the update law of the feedback controller is designed to ensure that every slave system synchronizes with master system. Finally, a numerical example is given to illustrate the effectiveness of the method and result obtained in this paper.