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Passivity of fractional-order coupled neural networks with interval uncertainties

Author

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  • Qiu, Hongling
  • Cao, Jinde
  • Liu, Heng

Abstract

This paper is mainly devoted to analyzing the passivity of two classes of uncertain fractional-order coupled neural networks (FCNNs) with different coupling dynamics. Compared with most FCNNs whose coupling dynamic is state coupling, a more generalized FCNN model with output coupling and interval uncertainties is proposed, which can treat the former as its special case. In addition, based on the linear matrix inequality technique, not only the passivity of FCNNs is discussed, but also several sufficient conditions that ensure input-strict passivity and output-strict passivity are given simultaneously. Not only that, the sufficient condition guaranteeing output-strict passivity can also realize the synchronization of FCNNs without input. Finally, two numerical simulations are provided to illustrate the rationality of the derived theoretical results.

Suggested Citation

  • Qiu, Hongling & Cao, Jinde & Liu, Heng, 2023. "Passivity of fractional-order coupled neural networks with interval uncertainties," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 205(C), pages 845-860.
  • Handle: RePEc:eee:matcom:v:205:y:2023:i:c:p:845-860
    DOI: 10.1016/j.matcom.2022.10.029
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    References listed on IDEAS

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    1. Padmaja, N. & Balasubramaniam, P., 2022. "Mixed H∞/passivity based stability analysis of fractional-order gene regulatory networks with variable delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 192(C), pages 167-181.
    2. Fang, Tian & Jiao, Shiyu & Fu, Dongmei & Su, Lei, 2021. "Passivity-based synchronization for Markov switched neural networks with time delays and the inertial term," Applied Mathematics and Computation, Elsevier, vol. 394(C).
    3. Li, Hong-Li & Kao, Yonggui & Hu, Cheng & Jiang, Haijun & Jiang, Yao-Lin, 2021. "Robust exponential stability of fractional-order coupled quaternion-valued neural networks with parametric uncertainties and impulsive effects," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    4. Zuñiga Aguilar, C.J. & Gómez-Aguilar, J.F. & Alvarado-Martínez, V.M. & Romero-Ugalde, H.M., 2020. "Fractional order neural networks for system identification," Chaos, Solitons & Fractals, Elsevier, vol. 130(C).
    5. Ning Li & Jinde Cao, 2016. "Passivity and robust synchronisation of switched interval coupled neural networks with time delay," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(12), pages 2827-2836, September.
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