Synchronization Control of Coupled Memristor-Based Neural Networks with Mixed Delays and Stochastic Perturbations

被引：22

作者：

Chen, Chuan ^{[1
]}

Li, Lixiang ^{[1
]}

Peng, Haipeng ^{[1
]}

Yang, Yixian ^{[1
,2
]}

Li, Tao ^{[3
]}

机构：

[1] Beijing Univ Posts & Telecommun, Informat Secur Ctr, State Key Lab Networking & Switching Technol, Beijing 100876, Peoples R China

[2] State Key Lab Publ Big Data, Guiyang 550025, Guizhou, Peoples R China

[3] Sichuan Univ, Coll Comp Sci, Chengdu 610065, Sichuan, Peoples R China

来源：

NEURAL PROCESSING LETTERS | 2018年 / 47卷 / 02期

基金：

中国国家自然科学基金;

关键词：

Synchronization; Stochastic perturbations; Mixed delays; Coupled memristor-based neural networks; Feedback controllers; TIME-VARYING DELAYS; EXPONENTIAL SYNCHRONIZATION; GLOBAL SYNCHRONIZATION; COMPLEX NETWORKS; STABILITY; ARRAY;

D O I：

10.1007/s11063-017-9675-6

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper investigates the synchronization control problem of coupled memristor-based neural networks (CMNNs) with mixed delays and stochastic perturbations. By utilizing simple feedback controllers, some novel sufficient conditions are derived to ensure the exponential synchronization of CMNNs with mixed delays and stochastic perturbations in mean square. In addition, by means of adaptive feedback controllers, the asymptotic synchronization of CMNNs with mixed delays and stochastic perturbations in mean square can also be achieved via stochastic LaSalle invariance principle. Numerical simulations are presented to illustrate the effectiveness of the theoretical results.

引用

页码：679 / 696

页数：18

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