Global Exponential Adaptive Synchronization of Complex Dynamical Networks With Neutral-Type Neural Network Nodes and Stochastic Disturbances
Global Exponential Adaptive Synchronization of Complex Dynamical Networks With Neutral-Type Neural Network Nodes and Stochastic Disturbances
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DOI：
10.1109/tcsi.2013.2249151
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发表时间：
2013-03
期刊：
影响因子：
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通讯作者：
Yijun Zhang;D. Gu;Shengyuan Xu
中科院分区：
文献类型：
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作者：
Yijun Zhang;D. Gu;Shengyuan Xu
研究了一类随机复杂动态网络的全局指数自适应同步设计问题。在所考虑的网络中，每个节点的动态近似的中性型神经网络。随机扰动描述的布朗运动。与以往文献不同的是，所考虑的自适应控制器的系数矩阵是任意矩阵而不是单位矩阵。利用李雅普诺夫方法和Kronecker积的一些性质，给出了保证所考虑网络的动力学与期望解在均方意义下全局指数同步的充分条件.进一步以推论的形式给出了具有一般节点的复杂动态网络全局指数自适应同步的一些判据。特别地，所提出的网络同步的标准是在线性矩阵不等式方面。每个准则中只使用两个变量，并且这些变量不在任何克罗内克积内。因此，条件很容易检查。数值算例表明了该方法的有效性和适用性。
This paper is on the design problem of global exponential adaptive synchronization for a class of stochastic complex dynamical networks. In the considered networks, the dynamics of each node are approximated by a neutral-type neural network. The stochastic disturbances are described in terms of Brownian motions. Different from the prior references, the coefficient matrix of the adaptive controller under consideration is an arbitrary matrix instead of an identity one. By using Lyapunov method and some properties of Kronecker product, a sufficient condition is proposed to ensure the dynamics of the considered network globally exponentially synchronize with the desired solution in the mean square sense. Some criteria for global exponential adaptive synchronization of complex dynamical networks with general nodes are further provided in forms of corollaries. In particular, the proposed criteria for network synchronization are in terms of linear matrix inequalities. Only two variables are used in each criterion and the variables are not inside of any Kronecker product. Hence, the conditions are easy to check. A numerical example is presented to show the effectiveness and applicability of the proposed approach.