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

Authors
Ali, M. SyedSaravanakumar, R.Ahn, Choon KiKarimi, Hamid Reza
Issue Date
May-2017
Publisher
ELSEVIER SCIENCE INC
Keywords
H-infinity filtering; Leakage delay; Linear matrix inequality; Stochastic neural networks; Time-varying delay
Citation
INFORMATION SCIENCES, v.388, pp.118 - 134
Indexed
SCIE
SCOPUS
Journal Title
INFORMATION SCIENCES
Volume
388
Start Page
118
End Page
134
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/83699
DOI
10.1016/j.ins.2017.01.010
ISSN
0020-0255
Abstract
This paper deals with the problem of H-infinity 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. (C) 2017 Elsevier Inc. All rights reserved.
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