Asymptotically almost periodic synchronization in fuzzy competitive neural networks with Caputo-Fabrizio operator

Abstract

This paper researches a class of Caputo-Fabrizio fractional-order fuzzy competitive neural networks (CF-FCNNs) with different time scales and time delays. Firstly, according to Banach contracting mapping principle and some appropriate assumptions, it derives CF-FCNNs possess a unique weak solution. Then, exponential Euler difference scheme of discrete-time CF-FCNNs (DCF-FCNNs) is presented by the constant variation methods and the difference format is implicit Euler difference and is solved by fractional PECE algorithm. Next, the existence of a unique bounded asymptotically almost periodic sequence solution, global exponential stability and synchronization of DCF-FCNNs are considered. In the end, numerical examples are given to describe the effectiveness of the acquired conclusions.