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Neural Processing Letters
Erschienen in: Neural Processing Letters 2/2015

01.10.2015

New Criteria on Delay-Dependent Robust Stability for Uncertain Markovian Stochastic Delayed Neural Networks

verfasst von: Huabin Chen, Jinjing Wang, Liu Wang

Erschienen in: Neural Processing Letters | Ausgabe 2/2015

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Abstract

This paper is mainly concerned about the problem of the robustly exponential stability of uncertain stochastic neural networks with time-varying delay and Markovian jump parameters. Some new delay-dependent stability criteria are established for the considered systems by constructing a modified Lyapunov–rasovskii functional, which are expressed in terms of linear matrix inequalities. Compared with some existing ones, our obtained results have a potential less conservatism. Finally, three illustrative numerical examples are provided to show the effectiveness of the obtained results.
Vorheriger Artikel Adaptive Agents in Changing Environments, the Role of Modularity
Nächster Artikel Soft Margin Based Low-Rank Audio Signal Classification

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Metadaten
Titel
New Criteria on Delay-Dependent Robust Stability for Uncertain Markovian Stochastic Delayed Neural Networks
verfasst von
Huabin Chen
Jinjing Wang
Liu Wang
Publikationsdatum
01.10.2015
Verlag
Springer US
Erschienen in
Neural Processing Letters / Ausgabe 2/2015
Print ISSN: 1370-4621
Elektronische ISSN: 1573-773X
DOI
https://doi.org/10.1007/s11063-014-9356-7

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