Analysis on global exponential robust stability of reaction–diffusion neural networks with S-type distributed delays

To avoid the unstable phenomena caused by time delays and perturbations, we investigate the sufficient conditions to ensure the global exponential robust stability with a convergence rate for the reaction–diffusion neural networks with S-type distributed delays. Because S-type distributed delays lea...

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Bibliographic Details
Published in:Physica. D 2008-04, Vol.237 (4), p.475-485
Main Authors: Liu, Puchen, Yi, Fengqi, Guo, Qiang, Yang, Jun, Wu, Wei
Format: Article
Language:English
Subjects:
Distributed delays
Exact sciences and technology
Exponential robust stability
Neural networks
Physics
Reaction–diffusion
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Summary:To avoid the unstable phenomena caused by time delays and perturbations, we investigate the sufficient conditions to ensure the global exponential robust stability with a convergence rate for the reaction–diffusion neural networks with S-type distributed delays. Because S-type distributed delays lead to some difficulty, we also introduce a new generalized Halanay inequality and a novel method–system-approximation method into the qualitative research of neural networks. Moreover, the sufficient criteria provided here, which are rather accessible and feasible, have wider adaptive range.
ISSN:0167-2789
1872-8022
DOI:10.1016/j.physd.2007.09.014