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New Criteria for Dissipativity Analysis of Fractional-Order Static Neural Networks

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Abstract

This paper deals with the dissipativity analysis problem for a class of fractional-order static neural networks (FOSNNs). We first derive a novel sufficient condition for global asymptotic stability of FOSNNs by constructing novel convex Lyapunov functions and using linear matrix inequality techniques. Then, based on the proposed stable criterion combined with some auxiliary properties of fractional calculus, the dissipative problem for the related system is solved for the first time. In addition, we also extend the obtained results to generalized fractional-order neural networks. Four numerical examples are provided to show the validity and effectiveness of the proposed results.

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Acknowledgements

The authors sincerely thank the associate editor and anonymous reviewers for their constructive comments that helped improve the quality and presentation of this paper. The research of Mai Viet Thuan is funded by the Ministry of Education and Training of Vietnam under Grant Number B2022-MDA-02. The research of Duong Thi Hong is supported by the International Mathematical Union (IMU) under the IMU Breakout Graduate Fellowship (IMU-BGF-2021-01) and the Thai Nguyen University level research topic (DH2021-TN06-05).

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Authors and Affiliations

  1. Department of Mathematics and Informatics, TNUS–University of Sciences, Thainguyen, Vietnam

    Duong Thi Hong & Mai Viet Thuan

  2. Faculty of Fundamental Science, Hanoi University of Industry, 298 Cau Dien Street, Bac Tu Liem District, Hanoi, Vietnam

    Nguyen Huu Sau

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  1. Duong Thi Hong
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Correspondence to Mai Viet Thuan.

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Hong, D.T., Sau, N.H. & Thuan, M.V. New Criteria for Dissipativity Analysis of Fractional-Order Static Neural Networks. Circuits Syst Signal Process 41, 2221–2243 (2022). https://doi.org/10.1007/s00034-021-01888-2

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