Exponential stochastic synchronization of coupled neural networks with adaptive intermittent control
作者单位：College of ScienceShenyang Jian Zhu University College of SciencesNortheastern University
会议名称：《第36届中国控制会议》
会议届次：36
主办单位：Dalian University of Technology;Systems Engineering Society of China (SESC);Technical Committee on Control Theory (TCCT), Chinese Association of Automation (CAA)
会议日期：2017年
学科分类：0711[理学-系统科学] 12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 071102[理学-系统分析与集成] 081103[工学-系统工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：supported by National Natural Science Foundation of China(Grant No 61673100) Liaoning Bai Qian Wan Talents Program(grant no.2017076) the Natural Science Foundation of Liaoning Province(Grant No20170540769) the Fundamental Research Funds for the Central Universities(N140504009) the Discipline Han Yu Project of Shenyang Jianzhu University(Grant No.XKHY2-104) the 9th group of Education Scientific Research Project Topics of Shenyang Jianzhu University(Grant No.20160124)
关 键 词：Coupled neural networks Chaotic delayed neural networks Exponential stochastic synchronization Adaptive periodically intermittent control
摘 要：In this paper, the exponential stochastic synchronization of coupled neural networks via adaptive periodically intermittent control is further investigated. Based on the Lyapunov stability theory combined with the method of the adaptive control,periodically intermittent control and the properties of Weiner process, some simple criteria are derived for the exponential stochastic synchronization of the coupled neural networks with coupling delays under stochastic perturbations. The adaptive periodically intermittent control which we have obtained can cut down control cost. The sufficient conditions of this paper for network synchronization are less conservative and can be applied in a wider area. The numerical example of the stochastically coupled neural networks is given to demonstrate the effectiveness of the control strategies.