Published March 14, 2005 | Version v1
Journal article

Global exponential stability and periodicity of cellular neural networks with variable delays

  • 1. Department of Mathematics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016 (China) and Department of Mathematics, Xinjiang Normal University, Urumqi 830054 (China)

Description

The Letter presents sufficient conditions ensuring the global exponential stability and existence of the periodic solution for cellular neural networks with variable delays. The results allow for the consideration of all unbounded neuron activation functions (but not necessarily surjective), in particular, can analyze the exponential stability and periodicity for the linear cellular neural networks. The work provides one such method which can be applied to cellular neural networks systems with variable delays. The method, based on the theory of fixed point and differential inequality technique. The applicability of the present results is demonstrated by two examples

Additional details

Identifiers

DOI
10.1016/j.physleta.2004.12.001;
PII
S0375-9601(04)01675-5;

Publishing Information

Journal Title
Physics Letters. A
Journal Volume
336
Journal Issue
4-5
Journal Page Range
p. 331-341
ISSN
0375-9601
CODEN
PYLAAG

INIS

Country of Publication
Netherlands
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
37033871
Subject category
S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
Descriptors DEI
FUNCTIONS; MATHEMATICAL SOLUTIONS; NERVE CELLS; NEURAL NETWORKS; PERIODICITY; STABILITY; TIME DELAY
Descriptors DEC
ANIMAL CELLS; SOMATIC CELLS; VARIATIONS

Optional Information

Copyright
Copyright (c) 2004 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.