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Finite-time stabilization of uncertain neural networks with distributed time-varying delays

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Abstract

In this paper, the problem of finite-time stabilization for a class of uncertain neural networks with distributed time-varying delays is investigated. Based on the Lyapunov stability theory and integral inequality technique, some sufficient LMI conditions are derived to ensure the finite-time stability of considered neural networks. In addition, the upper bound of the settling time for stabilization is estimated. Numerical simulations are carried out to demonstrate the effectiveness of the obtained results.

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Acknowledgments

This research is supported by the Natural Science Foundation of China (No: 61374078), Chongqing Research Program of Basic Research and Frontier Technology (No. cstc2015jcyjBX0052) and NPRP Grant # NPRP 4-1162-1-181 from the Qatar National Research Fund (a member of Qatar Foundation).

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Authors and Affiliations

  1. Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, College of Electronic and Information Engineering, Southwest University, Chongqing, 400715, China

    Shiju Yang & Chuandong Li

  2. Texas A&M University at Qatar, Doha, 23874, Qatar

    Tingwen Huang

Authors
  1. Shiju Yang
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  2. Chuandong Li
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  3. Tingwen Huang
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Correspondence to Chuandong Li.

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Yang, S., Li, C. & Huang, T. Finite-time stabilization of uncertain neural networks with distributed time-varying delays. Neural Comput & Applic 28 (Suppl 1), 1155–1163 (2017). https://doi.org/10.1007/s00521-016-2421-6

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  • DOI: https://doi.org/10.1007/s00521-016-2421-6

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