IEEE Trans Neural Netw Learn Syst. 2020 Oct;31(10):3777-3787. doi: 10.1109/TNNLS.2019.2946151. Epub 2019 Nov 15.
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.
本文研究了具有不确定交换信息的一类离散时间神经网络（NNs）的同步问题，这些不确定信息是由 NNs 节点之间的不确定连接权重引起的，并将其转换为范数有界不确定拉普拉斯矩阵。分布式脉冲观测器具有减少 NNs 节点之间通信负载的优点，被设计用来观测 NNs 的状态。提出了脉冲控制器来提高控制器的效率。基于矩阵克罗内克积，得到了脉冲增广误差系统（IAES）。通过证明 IAES 的稳定性，建立了一个充分条件来确保神经网络组的同步。给出了一个迭代算法来获得脉冲信号的最优允许区间，并推导出了观测器和控制器的相应增益。通过一个数值例子说明了所提出的结果。
