The Global Exponential Synchronization of Delayed Fuzzy Inertial Neural Networks via the Characteristics Method

Abstract

This study investigates the global exponential synchronization (GES) of delayed fuzzy inertial neural networks (DFINNs). Diverging from conventional approaches that rely on reduced order transformations and the construction of Lyapunov Krasovskii functionals (LKFs), we employ the characteristic method to derive GES criteria for DFINNs. We introduce three sufficient conditions, each expressed as a set of linear scalar inequalities. The validity of our theoretical findings is confirmed via a numerical example utilizing three distinct controllers, supported by corresponding simulation results.