Global Exponential Stability Analysis for Cohen-Grossberg Neural Networks with Non-Lipschitz Neuron Activations

Abstract:

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In this paper,a novel class of Cohen-Grossberg neural networks with inverse Hlder neuron activation functions is presented. By employing the Brouwer degree properties and linear matrix inequality techniques, the existence and uniqueness of equilibrium point for such Cohen-Grossberg neural networks are investigated. By constructing appropriate Lyapunov functions and using Lyapunov diagonally stable matrices, a sufficient condition which is used to checked the global exponential stability of a unique equilibrium point is established. A numerical example is given to demonstrate the effectiveness of the theoretical results.

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Periodical:

Edited by:

Qi Luo

Pages:

1136-1141

DOI:

10.4028/www.scientific.net/AMM.58-60.1136

Citation:

H. W. Xu "Global Exponential Stability Analysis for Cohen-Grossberg Neural Networks with Non-Lipschitz Neuron Activations", Applied Mechanics and Materials, Vols. 58-60, pp. 1136-1141, 2011

Online since:

June 2011

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$35.00

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