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  5. Stochastic H∞ filtering for neural networks with leakage delay and mixed time-varying delays

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Article
English
2017

Stochastic H∞ filtering for neural networks with leakage delay and mixed time-varying delays

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English
2017
Information Sciences
Vol 388-389
DOI: 10.1016/j.ins.2017.01.010

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Hamid Reza Karimi
Hamid Reza Karimi

Politecnico di Milano

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M. Syed Ali
Ramasamy Saravanakumar
Choon Ki Ahn
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Abstract

This paper deals with the problem of H ∞ filtering for stochastic neural networks (SNNs) with a mixed of time-varying interval delays, time-varying distributed delays, and leakage delays. A novel quintuple integral Lyapunov–Krasovskii functional (LKF) is constructed to improve the performance of the SNN. Sufficient criteria can be obtained by applying the linear matrix inequality (LMI) approach and developing a new mathematical analysis, which ensures the filtering error system is asymptotically stable in the mean square. Finally, simulation results are provided to show the superiority and usefulness of the proposed method.

How to cite this publication

M. Syed Ali, Ramasamy Saravanakumar, Choon Ki Ahn, Hamid Reza Karimi (2017). Stochastic H∞ filtering for neural networks with leakage delay and mixed time-varying delays. Information Sciences, 388-389, pp. 118-134, DOI: 10.1016/j.ins.2017.01.010.

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Publication Details

Type

Article

Year

2017

Authors

4

Datasets

0

Total Files

0

Language

English

Journal

Information Sciences

DOI

10.1016/j.ins.2017.01.010

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