Stability Analysis of Delayed Cellular Neural Networks With and Without Noise Perturbation

ZHANG Xue-juan; WANG Guan-xiang; LIU Hua

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ZHANG Xue-juan, WANG Guan-xiang, LIU Hua. Stability Analysis of Delayed Cellular Neural Networks With and Without Noise Perturbation[J]. Applied Mathematics and Mechanics, 2008, 29(11): 1293-1302.

Citation:

ZHANG Xue-juan, WANG Guan-xiang, LIU Hua. Stability Analysis of Delayed Cellular Neural Networks With and Without Noise Perturbation[J]. Applied Mathematics and Mechanics, 2008, 29(11): 1293-1302.

Citation:

ZHANG Xue-juan, WANG Guan-xiang, LIU Hua. Stability Analysis of Delayed Cellular Neural Networks With and Without Noise Perturbation[J]. Applied Mathematics and Mechanics, 2008, 29(11): 1293-1302.

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Stability Analysis of Delayed Cellular Neural Networks With and Without Noise Perturbation

1.
Department of Mathematics, Shaoxing University, Shaoxing, Zhejiang 312000, P. R. China;

Received Date: 2008-04-08
Rev Recd Date: 2008-08-28
Publish Date: 2008-11-15

Abstract

Abstract

The stability of a class of delayed cellular neural networks (DCNN) either without or with noise perturbation are studied. After presenting a simple and easily checkable condition for global exponential stability of the deterministic system, the situations with noise perturbation were further investigated. When the DCNN is perturbed with an external noise, the system is globally stable. The important fact is that, when the system is perturbed with an internal noise, it's globally exponentially stable if only the total strength of the noise is within a certain bound. This fact is significant as stochastic resonance phenomena have been found exist in many nonlinear systems.
- delayed cellular neural network,
- global exponent stability,
- external/internal noise

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References(15)

References

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