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首页> 外文期刊>Neural Networks and Learning Systems, IEEE Transactions on >Observer-Based Impulsive Synchronization for Neural Networks With Uncertain Exchanging Information
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Observer-Based Impulsive Synchronization for Neural Networks With Uncertain Exchanging Information

机译：基于观察者的神经网络脉冲同步，不确定交换信息

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摘要

This article investigates synchronization for a group of discrete-time neural networks (NNs) with the uncertain exchanging information, which is caused by the uncertain connection weights among the NNs nodes, and they are transformed into a norm-bounded uncertain Laplacian matrix. Distributed impulsive observers, which possess the advantage of reducing the communication load among NNs nodes, are designed to observe the NNs state. The impulsive controller is proposed to improve the efficiency of the controller. An impulsive augmented error system (IAES) is obtained based on the matrix Kronecker product. A sufficient condition is established to ensure synchronization of the group of NNs by proving the stability of the IAES. An iterative algorithm is given to obtain a suboptimal allowed interval of the impulsive signal, and the corresponding gains of the observer and the controller are derived. The developed result is illustrated by a numerical example.
机译：本文研究了一组离散时间神经网络（NNS）的同步，该信息与不确定的交换信息，这是由NNS节点中不确定的连接权重引起的，并且它们被转换成常态不确定的LAPLACIAN矩阵。具有降低NNS节点之间的通信负荷的分布式脉冲观察者旨在观察NNS状态。建议脉冲控制器提高控制器的效率。基于Matrix Kronecker产品获得脉冲增强的误差系统（IAE）。建立足够的条件以通过证明IAE的稳定性来确保NN组的同步。给出了一种迭代算法来获得脉冲信号的次优允许的间隔，并且导出观察者和控制器的相应增益。开发结果由数值示例说明。

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