New results on finite-time stability for fractional-order neural networks with proportional delay

This paper investigates the finite-time stability for a class of fractional-order neural networks with proportional delay. By some analytic techniques, a generalized Gronwall integral inequality with proportional delay is established. Based on this new inequality, a criterion is derived to guarantee...

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Bibliographic Details
Published in:Neurocomputing (Amsterdam) 2021-06, Vol.442, p.327-336
Main Authors: Yang, Zhanying, Zhang, Jie, Hu, Junhao, Mei, Jun
Format: Article
Language:English
Subjects:
Finite-time stability
Fractional-order system
Generalized Gronwall inequality
Neural network
Proportional delay
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Summary:This paper investigates the finite-time stability for a class of fractional-order neural networks with proportional delay. By some analytic techniques, a generalized Gronwall integral inequality with proportional delay is established. Based on this new inequality, a criterion is derived to guarantee the finite-time stability of systems when the fractional order is between 1 and 2. Moreover, when the fractional order is between 0 and 1, a new criterion is developed to ensure the finite-time stability of systems. This criterion is experimentally proved to be less conservative than those in the previous works. Finally, the effectiveness of our criteria is supported by some numerical examples.
ISSN:0925-2312
1872-8286
DOI:10.1016/j.neucom.2021.02.082