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Fixed-Time Synchronization of Coupled Discontinuous Neural Networks with Nonidentical Perturbations

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Abstract

This paper investigates fixed-time synchronization of coupled neural networks with discontinuous activation functions and nonidentical perturbations under the framework of Filippov solution. In order to overcome uncertainties of the Filippov solution and the effects of nonidentical perturbations, 1-norm based techniques are developed. By designing new state feedback controllers, constructing new Lyapunov functional, and utilizing differential inclusion theory, several sufficient conditions are obtained to ensure that the coupled discontinuous neural networks (CDNNs) to be synchronized in a fixed settling time. Results of this paper improve corresponding ones which only finite-time synchronization can be achieved for CDNNs. Finally, numerical simulations are offered to verify the effectiveness of the theoretical analysis.

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Authors and Affiliations

  1. College of Resources and Environment, Southwest University, Chongqing, 400715, China

    Xusen Zhu

  2. School of Economic and Management, Chongqing Normal University, Chongqing, 401331, China

    Xusen Zhu

  3. School of Mathematical Sciences, Chongqing Normal University, Chongqing, 401331, China

    Xinsong Yang

  4. Key Laboratory of Optimization and Control, Ministry of Education, Chongqing, 401331, China

    Xinsong Yang

  5. Faculty of Engineering, King Abdulaziz University, Jeddah, 21589, Saudi Arabia

    Fuad E. Alsaadi

  6. Department of Mathematics, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia

    Tasawar Hayat

  7. Department of Mathematics, Quaid-I-Azam University, Islamabad, Pakistan

    Tasawar Hayat

Authors
  1. Xusen Zhu
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  2. Xinsong Yang
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  3. Fuad E. Alsaadi
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  4. Tasawar Hayat
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Corresponding author

Correspondence to Xinsong Yang.

Additional information

This work was supported by the National Natural Science Foundation of China (NSFC) under Grant No. 61673078.

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Zhu, X., Yang, X., Alsaadi, F.E. et al. Fixed-Time Synchronization of Coupled Discontinuous Neural Networks with Nonidentical Perturbations. Neural Process Lett 48, 1161–1174 (2018). https://doi.org/10.1007/s11063-017-9770-8

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  • DOI: https://doi.org/10.1007/s11063-017-9770-8

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