Finite-Time and Fixed-Time Synchronization of Inertial Cohen-Grossberg-Type Neural Networks with Time Varying Delays

被引：39

作者：

Aouiti, Chaouki ^{[1
]}

Assali, El Abed ^{[1
]}

El Foutayeni, Youssef ^{[2
]}

机构：

[1] Univ Carthage, Fac Sci Bizerta, Dept Math, UR13ES47 Res Units Math & Applicat, Bizerte 7021, Tunisia

[2] Hassan II Univ Casablanca, Anal Modeling & Simulat Lab, Casablanca, Morocco

来源：

NEURAL PROCESSING LETTERS | 2019年 / 50卷 / 03期

关键词：

Inertial Cohen-Grossberg-type; Neural networks; Finite-time synchronization; Fixed-time synchronization; Time-varying delays; GLOBAL EXPONENTIAL STABILITY; MIXED DELAYS; SYSTEMS; STABILIZATION;

D O I：

10.1007/s11063-019-10018-8

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 is devoted to studying the finite-time and fixed-time of inertial Cohen-Grossberg type neural networks (ICGNNs) with time varying delays. First, by constructing a proper variable substitution, the original (ICGNNs) can be rewritten as first-order differential system. Second, by utilizing feedback controllers and constructing suitable Lyapunov functionals, several new sufficient conditions guaranteeing the finite-time and the fixed-time synchronization of ICGNNs with time varying delays are obtained based on different finite-time synchronization analysis techniques. The obtained sufficient conditions are simple and easy to verify. Numerical simulations are given to illustrate the effectiveness of the theoretical results.

引用

页码：2407 / 2436

页数：30

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