同步(交流)
控制理论(社会学)
网络拓扑
异步通信
计算机科学
伯努利原理
拓扑(电路)
联轴节(管道)
传输延迟
隐马尔可夫模型
人工神经网络
马尔可夫过程
集合(抽象数据类型)
网络数据包
数学
工程类
人工智能
控制(管理)
计算机网络
程序设计语言
机械工程
统计
航空航天工程
组合数学
操作系统
作者
Hui Chen,Y.H. Wang,Chang Liu,Zi‐Jing Xiao,Jie Tao
标识
DOI:10.1016/j.isatra.2024.01.022
摘要
The finite-time synchronization problem is studied for coupled neural networks (CNNs) with time-delay jumping coupling. Markovian switching topologies, imprecise delay models, uncertain parameters and the unavailable of topology modes are considered in this work. A mode-dependent delay with pre-known conditional probability is built to handle the imprecise delay model problem. A hidden Markov model with uncertain parameters is introduced to describe the mode mismatch problem, and an asynchronous controller is designed. Besides, a set of Bernoulli processes models the random packet dropouts during data communication. Based on Markovian switching topologies, mode-dependent delays, uncertain probabilities and packet dropout, a sufficient condition that guarantees the CNNs reach finite-time synchronization (FTS) is derived. Finally, a numerical example is derived to demonstrate the efficiency of the proposed synchronous technique.
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