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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 7/2012

01.10.2012 | Original Article

Global robust asymptotic stability analysis of uncertain switched Hopfield neural networks with time delay in the leakage term

verfasst von: P. Balasubramaniam, V. Vembarasan, R. Rakkiyappan

Erschienen in: Neural Computing and Applications | Ausgabe 7/2012

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Abstract

This paper deals with the problem of delay-dependent global robust asymptotic stability of uncertain switched Hopfield neural networks (USHNNs) with discrete interval and distributed time-varying delays and time delay in the leakage term. Some Lyapunov––Krasovskii functionals are constructed and the linear matrix inequality (LMI) approach are employed to derive some delay-dependent global robust stability criteria which guarantee the global robust asymptotic stability of the equilibrium point for all admissible parametric uncertainties. The proposed results that do not require the boundedness, differentiability, and monotonicity of the activation functions. Moreover, the stability behavior of USHNNs is very sensitive to the time delay in the leakage term. It can be easily checked via the LMI control toolbox in Matlab. In the absence of leakage delay, the results obtained are also new results. Finally, nine numerical examples are given to show the effectiveness of the proposed results.
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Metadaten
Titel
Global robust asymptotic stability analysis of uncertain switched Hopfield neural networks with time delay in the leakage term
verfasst von
P. Balasubramaniam
V. Vembarasan
R. Rakkiyappan
Publikationsdatum
01.10.2012
Verlag
Springer-Verlag
Erschienen in
Neural Computing and Applications / Ausgabe 7/2012
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-011-0639-x

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