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

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• 作者：M. Syed Ali^a ; R. Saravanakumar^a ; ^b ; Choon Ki Ahn ; ^c ; ^{hironaka@korea.ac.kr} ; Hamid Reza Karimi^d
• 关键词：H&infin ; filtering ; Leakage delay ; Linear matrix inequality ; Stochastic neural networks ; Time-varying delay
• 刊名：Information Sciences
• 出版年：2017
• 出版时间：May 2017
• 年：2017
• 卷：388-389
• 期：Complete
• 页码：118-134
• 全文大小：849 K
• 卷排序：388

文摘

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.