Published February 13, 2006
| Version v1
Journal article
Global exponential robust stability of reaction-diffusion interval neural networks with time-varying delays
Creators
- 1. Departament of Mathematics, Ocean University of China, Qingdao 266071 (China) and Departament of Mathematics, Liaocheng University, Liaocheng 252059 (China)
- 2. Chemical College, Anshan University of Science and Technology, Anshan 114000 (China)
Description
The authors discuss the existence of the equilibrium point and its global exponential robust stability for reaction-diffusion interval neural networks with time-varying delays by means of the topological degree theory and Lyapunov-functional method. Since the diffusion phenomena, time delay and the perturbation due to noises as well as some unforced man-made faults could not be ignored in neural networks, the model presented here is close to the actual systems, and the sufficient conditions on global exponential robust stability established in this Letter, which are easily verifiable, have a wider adaptive range
Additional details
Identifiers
- DOI
- 10.1016/j.physleta.2005.10.031;
- PII
- S0375-9601(05)01597-5;
Publishing Information
- Journal Title
- Physics Letters. A
- Journal Volume
- 350
- Journal Issue
- 5-6
- Journal Page Range
- p. 342-348
- ISSN
- 0375-9601
- CODEN
- PYLAAG
INIS
- Country of Publication
- Netherlands
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 37066282
- Subject category
- S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
- Descriptors DEI
- EQUILIBRIUM; LYAPUNOV METHOD; NEURAL NETWORKS; NOISE; PERTURBATION THEORY; STABILITY; TIME DELAY; TOPOLOGY
- Descriptors DEC
- CALCULATION METHODS; MATHEMATICS
Optional Information
- Copyright
- Copyright (c) 2005 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.