Uniformly stable and attractive of fractional-order memristor-based neural networks with multiple delays

Xueqi Yao, Shouming Zhong, Taotao Hu, Hong Cheng and Dian Zhang

Applied Mathematics and Computation, 2019, vol. 347, issue C, 392-403

Abstract: Memristive neural networks (MNN) have been wildly studied. Nevertheless, fractional -order memristive neural networks (FMNN) still remain a wide-open dilemma. This paper addresses the problem of FMNN systems with multiple delays and grew several related theories through the study. First, the existence of the system equilibrium point is investigated based on contraction mapping principle, and a new sufficient criterion is obtained. Second, the delay-free uniform stability of the system is discussed by employing differential inclusion theory. Third, a novel asymptotic stability criterion is proposed which is less conservative. Finally, one descriptive numerical example and simulation results emphasize the accuracy and reliability of the proposed results.

Keywords: Fractional-order systems; Memristive neural networks; Multiple delays; Uniformly stable; Attractive (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:347:y:2019:i:c:p:392-403

DOI: 10.1016/j.amc.2018.11.028

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