Published November 5, 2007
| Version v1
Journal article
Global exponential stability of BAM neural networks with time-varying delays and diffusion terms
Creators
- 1. Department of Mathematics and Physics, Wuhan University of Science and Engineering, Wuhan 430073 (China)
- 2. Department of Mathematics, Nanjing University, Nanjing 210008 (China)
Description
The stability property of bidirectional associate memory (BAM) neural networks with time-varying delays and diffusion terms are considered. By using the method of variation parameter and inequality technique, the delay-independent sufficient conditions to guarantee the uniqueness and global exponential stability of the equilibrium solution of such networks are established
Availability note (English)
Available from http://dx.doi.org/10.1016/j.physleta.2007.06.008Additional details
Identifiers
- DOI
- 10.1016/j.physleta.2007.06.008;
- PII
- S0375-9601(07)00857-2;
Publishing Information
- Journal Title
- Physics Letters. A
- Journal Volume
- 371
- Journal Issue
- 1-2
- Journal Page Range
- p. 83-89
- ISSN
- 0375-9601
- CODEN
- PYLAAG
INIS
- Country of Publication
- Netherlands
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 39085237
- Subject category
- S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
- Descriptors DEI
- CALCULATION METHODS; DIFFUSION; EQUILIBRIUM; NEURAL NETWORKS; STABILITY; VARIATIONS
Optional Information
- Copyright
- Copyright (c) 2007 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.