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New Result on Finite-Time Stability for Caputo–Katugampola Fractional-Order Neural Networks with Time Delay

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Abstract

In this paper, with the help of beta function, a new fractional-order Gronwall integral inequality is established to investigate the existence, uniqueness and finite-time stability of zero solution of a class of Caputo–Katugampola fractional-order neural networks with time delay. In view of this inequality, a new result to ensure the finite-time stability of system with fractional order between 0 and 1 is obtained. In certain circumstances, it is demonstrated by experiments that the result is less conservative than those in the existing papers. At last, two numerical examples are used for indicating the validity of the presented results.

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Authors and Affiliations

  1. School of Mathematics and Statistics, Hunan Normal University, Changsha, 410081, Hunan, People’s Republic of China

    Shuihong Xiao

  2. Key Laboratory of High Performance Computing and Stochastic Information Processing, Hunan Normal University, Changsha, 410081, Hunan, People’s Republic of China

    Jianli Li

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  1. Shuihong Xiao
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  2. Jianli Li
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This work is supported by the NNSF of China (12071105).

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Xiao, S., Li, J. New Result on Finite-Time Stability for Caputo–Katugampola Fractional-Order Neural Networks with Time Delay. Neural Process Lett 55, 7951–7966 (2023). https://doi.org/10.1007/s11063-023-11291-4

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