Published July 18, 2005 | Version v1
Journal article

Global asymptotic stability of Cohen-Grossberg neural network with continuously distributed delays

  • 1. Department of Mathematics, Nanjing University, Nanjing 210008 (China)

Description

The convergence dynamical behaviors of Cohen-Grossberg neural network with continuously distributed delays are discussed. By using Brouwer's fixed point theorem, matrix theory and analysis techniques such as Gronwall inequality, some new sufficient conditions guaranteeing the existence, uniqueness of an equilibrium point and its global asymptotic stability are obtained. An example is given to illustrate the theoretical results

Additional details

Identifiers

DOI
10.1016/j.physleta.2005.05.026;
PII
S0375-9601(05)00726-7;

Publishing Information

Journal Title
Physics Letters. A
Journal Volume
342
Journal Issue
4
Journal Page Range
p. 331-340
ISSN
0375-9601
CODEN
PYLAAG

INIS

Country of Publication
Netherlands
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
37036880
Subject category
S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
Descriptors DEI
CONVERGENCE; EQUILIBRIUM; NEURAL NETWORKS; STABILITY; TIME DELAY

Optional Information

Copyright
Copyright (c) 2005 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.