Journal
INFORMATION SCIENCES
Volume 180, Issue 20, Pages 4022-4030Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2010.06.033
Keywords
Neural networks; Cohen-Grossberg model; Inverse Holder functions; Topological degree; Global exponential stability
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Funding
- National Science Foundation of China [60772079]
- National S&T Major Project of China [2008ZX05020]
- Hebei Science Foundation of China [2010001297]
- Hebei Province Education Foundation of China [2009157]
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In this paper, a novel class of Cohen-Grossberg neural networks with delays and inverse Holder neuron activation functions are presented. By using the topological degree theory and linear matrix inequality (LMI) technique, the existence and uniqueness of equilibrium point for such Cohen-Grossberg neural networks is investigated. By constructing appropriate Lyapunov function, a sufficient condition which ensures the global exponential stability of the equilibrium point is established. Two numerical examples are provided to demonstrate the effectiveness of the theoretical results. (C) 2010 Elsevier Inc. All rights reserved.
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