同步(交流)
非线性系统
联轴节(管道)
控制理论(社会学)
Lyapunov稳定性
人工神经网络
期限(时间)
计算机科学
图论
拓扑(电路)
集合(抽象数据类型)
理论(学习稳定性)
数学
人工智能
物理
工程类
控制(管理)
量子力学
组合数学
机械工程
机器学习
程序设计语言
作者
Shaofu Yang,Zhenyuan Guo,Jun Wang
标识
DOI:10.1109/tsmc.2014.2388199
摘要
This paper is concerned with the global robust synchronization of multiple memristive neural networks (MMNNs) with nonidentical uncertain parameters. A coupling scheme is introduced, in a general topological structure described by a direct or undirect graph, with a linear diffusive term and a discontinuous sign term. First, a set of sufficient conditions are derived based on the Lyapunov stability theory for ascertaining global robust synchronization of coupled MMNNs. Second, a pinning adaptive coupling method is proposed to ensure global synchronization without knowing the bound of parameter uncertainties. Two illustrative examples are discussed to substantiate the theoretical results.
科研通智能强力驱动
Strongly Powered by AbleSci AI