Published July 18, 2005
| Version v1
Journal article
Global asymptotic stability of Cohen-Grossberg neural network with continuously distributed delays
Creators
- 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.