Matrix measure strategies for stability and synchronization of inertial BAM neural network with time delays
Matrix measure strategies for stability and synchronization of inertial BAM neural network with time delays
复制标题
时滞惯性BAM神经网络稳定性和同步性的矩阵测度策略
DOI：
10.1016/j.neunet.2014.02.003
复制
发表时间：
2014-05-01
期刊：
影响因子：
7.8
通讯作者：
Wan, Ying
中科院分区：
文献类型：
--
作者：
Cao, Jinde;Wan, Ying
本文研究一个具有时变时滞和外部输入的单惯性BAM神经网络。首先，通过选择合适的变量代换，原始系统可转化为一阶微分方程。然后，利用矩阵测度和哈拉奈不等式，我们给出了平衡点全局指数稳定的几个充分条件，这些准则形式简单且在实际中易于验证。此外，当在响应神经网络中采用误差反馈控制项时，也得到了关于驱动 - 响应神经网络指数同步的平行准则。最后，给出一些例子来说明我们的理论结果。© 2014爱思唯尔有限公司。保留所有权利。
A single inertial BAM neural network with time-varying delays and external inputs is concerned in this paper. First, by choosing suitable variable substitution, the original system can be transformed into first-order differential equations. Then, we present several sufficient conditions for the global exponential stability of the equilibrium by using matrix measure and Halanay inequality, these criteria are simple in form and easy to verify in practice. Furthermore, when employing an error-feedback control term to the response neural network, parallel criteria regarding to the exponential synchronization of the drive-response neural network are also generated. Finally, some examples are given to illustrate our theoretical results. (C) 2014 Elsevier Ltd. All rights reserved.