New results on synchronization for second-order fuzzy memristive neural networks with time-varying and infinite distributed delays

作者:

Highlights:

摘要

Without converting the second order terms to the first order ones, this article deals with the global asymptotic synchronization of second-order fuzzy memristive neural networks (SFMNNs) with infinite distributed and time-varying delays by contriving feedback control and adaptive control schemes. Based on Lyapunov stability theory, Barbalat Lemma and some analysis strategies, several new criteria in lights of algebraic inequalities are directly acquired to assure the global asymptotic synchronization of the concerned SFMNNs. Besides, compared with the existing reduced-order means, the global asymptotic synchronization is directly analyzed via accepting some new Lyapunov–Krasovskii functionals without the reduced-order means. Ultimately, some examples are provided to identify the availability of the theoretical outcomes.

论文关键词:Fuzzy neural network,Memristor,Synchronization,Feedback control,Adaptive control,Infinite distributed delay

论文评审过程:Received 6 May 2021, Revised 7 July 2021, Accepted 12 August 2021, Available online 16 August 2021, Version of Record 24 August 2021.

论文官网地址:https://doi.org/10.1016/j.knosys.2021.107397