独特性
指数稳定性
双向联想存储器
数学
平衡点
同胚(图论)
记忆电阻器
应用数学
人工神经网络
微分包含
理论(学习稳定性)
基质(化学分析)
M矩阵
内容寻址存储器
指数二分法
李雅普诺夫函数
指数函数
微分方程
数学分析
计算机科学
纯数学
离散数学
非线性系统
人工智能
物理
量子力学
机器学习
材料科学
工程类
可逆矩阵
电气工程
复合材料
作者
Runan Guo,Ziye Zhang,Xiaoping Liu,Chong Lin
标识
DOI:10.1016/j.amc.2017.05.021
摘要
This article explores the exponential stability problem of complex-valued bidirectional associative memory (BAM) neural networks with time delays. This analysis is on the basis of the M-matrix approach, the differential inclusions theory and the homeomorphism property. By constructing a novel Lyapunov functional, a sufficient criterion for the existence, uniqueness, and exponential stability for the equilibrium point of the considered system is derived. Moreover, similar results in terms of M-matrix are also obtained for the exponential stability problem of delayed complex-valued BAM neural networks without memristors. In the end, two numerical examples are provided to demonstrate the availability of the obtained results.
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