Novel results on bifurcation for a fractional-order complex-valued neural network with leakage delay

Jun Yuan, Lingzhi Zhao, Chengdai Huang and Min Xiao

Physica A: Statistical Mechanics and its Applications, 2019, vol. 514, issue C, 868-883

Abstract: This paper primarily investigates the impact of leakage delay on bifurcation for a fractional-order complex-valued neural network. By means of time delay as a bifurcation parameter, the bifurcation conditions are precisely determined of the proposed novel system. It is pointed out that the stability performance of the addressed fractional neural network is extremely undermined when leakage delay appears by utilizing comparative numerical analysis, they cannot be discarded. Our obtained results enormously generalizes and enhances the existing ones in literatures. Numerical simulations are presented to verify the validity of the obtained results.

Keywords: Leakage delays; Stability; Hopf bifurcation; Fractional order; Complex-valued neural networks (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:514:y:2019:i:c:p:868-883

DOI: 10.1016/j.physa.2018.09.138

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