4.7 Article

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

期刊

INFORMATION SCIENCES
卷 388, 期 -, 页码 118-134

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2017.01.010

关键词

H-infinity filtering; Leakage delay; Linear matrix inequality; Stochastic neural networks; Time-varying delay

资金

  1. Thailand Research Fund (TRF) [RSA5980019]
  2. Higher Education Commission
  3. National Research Foundation of Korea (NRF) - Ministry of Science, ICT & Future Planning [NRF-2014R1A1A1006101]
  4. Faculty of Science, Maejo University, Thailand

向作者/读者索取更多资源

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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