Quasi-synchronization of heterogeneous neural networks with distributed and proportional delays via impulsive control

Ruiyuan Zhu, Yingxin Guo and Fei Wang

Chaos, Solitons & Fractals, 2020, vol. 141, issue C

Abstract: In this paper, we discuss the quasi-synchronization of delayed heterogeneous dynamic neural networks based on impulsive control. The main difference of this paper with previous works on quasi-synchronization is that both proportional delay and distributed delay are considered. By establishing a novel impulsive delay inequality, combining Lyapunov theory and the concept of average impulsive interval, some necessary items for quasi-synchronization of delayed heterogeneous dynamic neural networks are obtained. Moreover, through using the generalized formulae for the variation of proportional and distributed delay parameters, the theoretical error bounded of quasi-synchronization is estimated. Finally, numerical examples are listed to explain the validity of our results.

Keywords: Neural networks (NNs); Complex quasi-synchronization; Proportional delay; Distributed-delay; Impulsive control (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:141:y:2020:i:c:s0960077920307165

DOI: 10.1016/j.chaos.2020.110322

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