独特性
同胚(图论)
类型(生物学)
人工神经网络
双向联想存储器
平衡点
数学
指数稳定性
控制理论(社会学)
理论(学习稳定性)
集合(抽象数据类型)
应用数学
拓扑(电路)
计算机科学
纯数学
内容寻址存储器
离散数学
数学分析
非线性系统
控制(管理)
微分方程
人工智能
组合数学
物理
机器学习
生物
程序设计语言
量子力学
生态学
作者
Desheng Xu,Manchun Tan
出处
期刊:Nonlinear Dynamics
[Springer Science+Business Media]
日期:2017-03-25
卷期号:89 (2): 819-832
被引量:28
标识
DOI:10.1007/s11071-017-3486-1
摘要
This paper focuses on the global asymptotic stability of complex-valued bidirectional associative memory (BAM) neutral-type neural networks with time delays. By virtue of homeomorphism theory, inequality techniques and Lyapunov functional, a set of delay-independent sufficient conditions is established for assuring the existence, uniqueness and global asymptotic stability of an equilibrium point of the considered complex-valued BAM neutral-type neural network model. The assumption on boundedness of the activation functions is not required, and the LMI-based criteria are easy to be checked and executed in practice. Finally, we give one example with simulation to show the applicability and effectiveness of our main results.
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