Synchronization and synchronized periodic solution in a simplified five-neuron BAM neural network with delays

被引：24

作者：

Ge, Juhong ^{[1
]}

Xu, Jian ^{[1
]}

机构：

[1] Tongji Univ, Sch Aerosp Engn & Appl Mech, Shanghai 200092, Peoples R China

来源：

NEUROCOMPUTING | 2011年 / 74卷 / 06期

基金：

美国国家科学基金会;

关键词：

Time delay; Global attractivity; Synchronized periodic solution; BAM neural network; BIDIRECTIONAL ASSOCIATIVE MEMORY; GLOBAL ASYMPTOTIC STABILITY; TIME-VARYING DELAYS; EXPONENTIAL STABILITY; BIFURCATION-ANALYSIS; HOPF-BIFURCATION; IDENTICAL CELLS; NEURONS; OSCILLATIONS; PATTERNS;

D O I：

10.1016/j.neucom.2010.11.017

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A delay-differential equation, modeling a bidirectional associative memory (BAM) neural network with five neurons, is considered. Some results of synchronization and bifurcation are exhibited. By Lyapunov functional methods, some sufficient conditions for the absolute synchronization of the system and global attractivity of the trivial solution are established. This synchronization is independent of the size of time delay. Furthermore, delay-induced synchronized periodic solution is given analytically, as well as necessary and sufficient conditions for the synchronized periodic solution by perturbation-incremental scheme (PIS). The main difference in this paper from previous works in the literatures is that delay-induced synchronization is studied quantitatively. Theoretical results are illustrated with numerical simulations. (C) 2010 Elsevier B.V. All rights reserved.

引用

页码：993 / 999

页数：7

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