Quasi-uniform synchronization of Caputo type fractional neural networks with leakage and discrete delays★

Hai Zhang, Jingshun Cheng, Hongmei Zhang, Weiwei Zhang and Jinde Cao

Chaos, Solitons & Fractals, 2021, vol. 152, issue C

Abstract: This paper discusses the quasi-uniform synchronization issue for fractional-orderneural networks (FONNs) with leakage and discrete delays. The impacts of leakage delay, discrete delay and fractional derivative on the quasi-uniform synchronization are simultaneously considered. By employing the Laplace transformation, the Gronwall inequality and analytical techniques, several sufficient criteria of the quasi-uniform synchronization for FONNs with leakage and discrete delays are established. The criterion conditions reveal the less conservatism because the order of fractional derivative is in the interval (0,2). The presented results are related to the classical exponential function, where it is not necessary to calculate fractional-order derivatives to reduce the complexities. Taking into account the different orders of fractional derivative, the validity and applicability of the proposed results are verified by the numerical simulations.

Keywords: Leakage delay; Fractional neural networks; Quasi-uniform synchronization; Laplace transformation (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:152:y:2021:i:c:s0960077921007864

DOI: 10.1016/j.chaos.2021.111432

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