4.7 Article

Novel results on passivity and exponential passivity for multiple discrete delayed neutral-type neural networks with leakage and distributed time-delays

期刊

CHAOS SOLITONS & FRACTALS
卷 115, 期 -, 页码 268-282

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chaos.2018.07.008

关键词

Neural networks; Lyapunov-Krasovskii functional; Passivity; Neutral-type neural networks; Linear matrix inequality; Exponential passivity; Distributed time-delays; Multiple discrete delays; Neutral delays; Leakage delays

资金

  1. Rajiv Gandhi National Fellowship under the University Grant Commission, New Delhi [F1-17.1/2016-17/RGNF-2015-17-SC-TAM-21509]
  2. Jiangsu Provincial Key Labo-ratory of Networked Collective Intelligence [BM2017002]
  3. Thailand research grant fund [RSA5980019]
  4. Maejo University

向作者/读者索取更多资源

This paper investigates the problem of passivity and exponential passivity for neutral-type neural networks (NNNs) with leakage, multiple discrete delay and distributed time-delay, via some novel sufficient conditions. Based on an appropriate Lyapunov-Krasovskii functional (LKF), free weighting matrix approach and some inequality techniques, enhanced passivity criteria for the concerned neural networks is established in the form of Linear matrix inequalities (LMIs). The feasibility of the attained passivity and exponential passivity criterions easily verified by the aid of LMI control toolbox in MATLAB software. Furthermore, we have compared our method with previous one in the existing literature, which depicts its less conservativeness. To substantiate the superiority and effectiveness of our analytical design, two examples with their numerical simulations are provided. (C) 2018 Elsevier Ltd. All rights reserved.

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