Absolute stability and synchronization in neural field models with transmission delays

被引：3

作者：

Kao, Chiu-Yen ^{[1
]}

Shih, Chih-Wen ^{[2
]}

Wu, Chang-Hong ^{[3
]}

机构：

[1] Claremont Mckenna Coll, Dept Math Sci, Claremont, CA 91711 USA

[2] Natl Chiao Tung Univ, Dept Appl Math, Hsinchu 300, Taiwan

[3] Natl Univ Tainan, Dept Appl Math, Tainan 700, Taiwan

来源：

PHYSICA D-NONLINEAR PHENOMENA | 2016年 / 328卷

基金：

美国国家科学基金会;

关键词：

Absolute stability; Synchronization; Neural field models; Delay equations; WAVE-PROPAGATION FAILURE; STATIONARY SOLUTIONS; TRAVELING FRONTS; STANDING PULSES; EXISTENCE; NETWORKS; BIFURCATIONS; EQUATIONS; DYNAMICS; BUMPS;

D O I：

10.1016/j.physd.2016.04.014

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Neural fields model macroscopic parts of the cortex which involve several populations of neurons. We consider a class of neural field models which are represented by integro-differential equations with transmission time delays which are space-dependent. The considered domains underlying the systems can be bounded or unbounded. A new approach, called sequential contracting, instead of the conventional Lyapunov functional technique, is employed to investigate the global dynamics of such systems. Sufficient conditions for the absolute stability and synchronization of the systems are established. Several numerical examples are presented to demonstrate the theoretical results. (C) 2016 Elsevier B.V. All rights reserved.

引用

页码：21 / 33

页数：13

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