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

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. (C) 2021 Elsevier B.V. All rights reserved.

Automated summary

This article studies the global asymptotic synchronization of second-order fuzzy memristive neural networks with infinite distributed and time-varying delays through feedback control and adaptive control schemes. New criteria are directly acquired based on Lyapunov stability theory and Barbalat Lemma to ensure the synchronization. The global asymptotic synchronization is directly analyzed via new Lyapunov-Krasovskii functionals without reduced-order means, compared to existing methods.