Finite-Time Synchronization for Fractional Order Fuzzy Inertial Cellular Neural Networks with Piecewise Activations and Mixed Delays

Abstract

This paper investigates a class of finite-time synchronization problems of fractional order fuzzy inertial cellular neural networks (FFICNNs) with piecewise activations and mixed delays. First, the Caputo FFICNNs are established. A suitable transformation variable is constructed to rewrite FFICNNs with mixed delays into a first-order differential system. Secondly, some new effective criteria are constructed on the basis of the finite-time stability theory and Lyapunov functionals to realize the synchronization of the drive-response system. Finally, two numerical simulation examples show that the proposed method is effective.

Asymptotic and Mittag–Leffler Synchronization of Fractional-Order Octonion-Valued Neural Networks with Neutral-Type and Mixed Delays

“…Then, the equivalent of the exponential stability and synchronization from integer-order neural networks, namely Mittag-Leffler stability and synchronization, were discussed in [28][29][30][31][32][33]. Finite-time stability and synchronization have been the focus of the papers [34][35][36][37][38][39]. Other dynamic properties were also studied, for example, dissipativity, in [40][41][42][43][44][45], etc.…”

“…When they appear together with time-varying delays, distributed delays are called mixed delays. FONNs with this type of delays have been discussed in the recent literature, for example, in [21,26,31,39,47,[51][52][53][54][55][56].…”