Robust stability of fractional-order memristor-based Hopfield neural networks with parameter disturbances

Shuxin Liu, Yongguang Yu, Shuo Zhang and Yuting Zhang

Physica A: Statistical Mechanics and its Applications, 2018, vol. 509, issue C, 845-854

Abstract: The robust stability of fractional-order memristor-based Hopfield neural networks (FMHNNs) with parameter disturbances is addressed in this paper. Based on the fractional-order Lyapunov direct method, some sufficient conditions on the robust stability are established. For such neural system with discontinuous right-hand sides, its existence and uniqueness of the equilibrium point are analyzed in the Filippov sense and the robust stability is also achieved. Finally, the numerical example is given to show the effectiveness of the proposed method.

Keywords: Memristor; Fractional-order Hopfield neural networks; Robust stability (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:509:y:2018:i:c:p:845-854

DOI: 10.1016/j.physa.2018.06.048

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