Stability of cellular neural networks with distributive time delays and noise perturbations

Cheng Hsiung Hsu; Tzi Sheng Yang

doi:10.1142/S0218127407017409

Stability of cellular neural networks with distributive time delays and noise perturbations

Cheng Hsiung Hsu, Tzi Sheng Yang

Department of Mathematics

Research output: Contribution to journal › Article › peer-review

Abstract

This work investigates the global stability of cellular neural networks with distributive time delays and noise perturbations. Two types of noise perturbations are considered in the system, one is internal noise and another is external noise. We show that the deterministic system preserves the globally exponential stability when it is perturbed by the internal noise with small noise strength. On the other hand, the deterministic system can only preserve weaker stability when it is perturbed by the external noise. We also provide some numerical simulations to support our theoretical analysis.

Original language	English
Pages (from-to)	535-544
Number of pages	10
Journal	International Journal of Bifurcation and Chaos in Applied Sciences and Engineering
Volume	17
Issue number	2
DOIs	https://doi.org/10.1142/S0218127407017409
State	Published - Feb 2007

Keywords

Absorbing regions
Brownian motion
Gaussian white noise
Ornstein-Uhlenbeck process

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10.1142/S0218127407017409

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author = "Hsu, {Cheng Hsiung} and Yang, {Tzi Sheng}",

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AU - Yang, Tzi Sheng

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PY - 2007/2

Y1 - 2007/2

N2 - This work investigates the global stability of cellular neural networks with distributive time delays and noise perturbations. Two types of noise perturbations are considered in the system, one is internal noise and another is external noise. We show that the deterministic system preserves the globally exponential stability when it is perturbed by the internal noise with small noise strength. On the other hand, the deterministic system can only preserve weaker stability when it is perturbed by the external noise. We also provide some numerical simulations to support our theoretical analysis.

AB - This work investigates the global stability of cellular neural networks with distributive time delays and noise perturbations. Two types of noise perturbations are considered in the system, one is internal noise and another is external noise. We show that the deterministic system preserves the globally exponential stability when it is perturbed by the internal noise with small noise strength. On the other hand, the deterministic system can only preserve weaker stability when it is perturbed by the external noise. We also provide some numerical simulations to support our theoretical analysis.

KW - Absorbing regions

KW - Brownian motion

KW - Gaussian white noise

KW - Ornstein-Uhlenbeck process

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JO - International Journal of Bifurcation and Chaos in Applied Sciences and Engineering

JF - International Journal of Bifurcation and Chaos in Applied Sciences and Engineering

IS - 2

ER -

Stability of cellular neural networks with distributive time delays and noise perturbations

Abstract

Keywords

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