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Delay-Independent Stability of Riemann–Liouville Fractional Neutral-Type Delayed Neural Networks

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Abstract

This paper is concerned with the delay-independent stability of Riemann–Liouville fractional-order neutral-type delayed neural networks. By constructing a suitable Lyapunov functional associated with fractional integral and fractional derivative terms, several sufficient conditions to ensure delay-independent asymptotic stability of the equilibrium point are obtained. The presented results are easily checked as they are described as the matrix inequalities or algebraic inequalities in terms of the networks parameters only. Two numerical examples are also given to show the validity and feasibility of the theoretical results.

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Acknowledgements

The authors are very grateful to the Editors, and the anonymous reviewers for their helpful and valuable comments and suggestions which improved the quality of the paper.

Author information

Authors and Affiliations

  1. School of Mathematics and Computation Science, Anqing Normal University, Anqing, 246133, China

    Hai Zhang & Renyu Ye

  2. College of Science, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China

    Renyu Ye

  3. School of Mathematics, and Research Center for Complex Systems and Network Sciences, Southeast University, Nanjing, 210096, China

    Jinde Cao

  4. Department of Mathematics, Faculty of Science, King Abdulaziz University, Jeddah, 21589, Saudi Arabia

    Jinde Cao

  5. Nonlinear Analysis and Applied Mathematics (NAAM) Research Group, and Department of Mathematics, King Abdulaziz University, Jeddah, 21589, Saudi Arabia

    Ahmed Alsaedi

Authors
  1. Hai Zhang
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  2. Renyu Ye
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  3. Jinde Cao
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  4. Ahmed Alsaedi
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Corresponding author

Correspondence to Hai Zhang.

Additional information

This work is jointly supported by National Natural Science Fund of China (11301308, 61573096, 61272530), the 333 Engineering Fund of Jiangsu Province of China (BRA2015286), the Natural Science Fund of Anhui Province of China (1608085MA14), the Key Project of Natural Science Research of Anhui Higher Education Institutions of China (gxyqZD2016205, KJ2015A152), and the Natural Science Youth Fund of Jiangsu Province of China (BK20160660).

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Zhang, H., Ye, R., Cao, J. et al. Delay-Independent Stability of Riemann–Liouville Fractional Neutral-Type Delayed Neural Networks. Neural Process Lett 47, 427–442 (2018). https://doi.org/10.1007/s11063-017-9658-7

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  • DOI: https://doi.org/10.1007/s11063-017-9658-7

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