Finite-Time Dissipative Synchronization for Markovian Jump Generalized Inertial Neural Networks With Reaction-Diffusion Terms

Abstract

A novel generalized neural network (NN), which includes Markovian jump parameters, inertial items, and reaction-diffusion terms, is proposed, and the issue of finite-time dissipative synchronization for this kind of NNs is discussed in this article. First, an appropriate variable substitution is employed so that the original second-order differential system is transformed into a first-order one. Second, a novel time-varying memory-based controller is designed to ensure the dissipative synchronization of the drive and response systems over a finite-time interval. Then, a new Lyapunov-Krasovskii function is processed by reciprocally convex combination and free-weighting matrix methods, therefore, a less conservative synchronization criterion is derived. Finally, by providing three examples, the feasibility, superiority, and practicality of the obtained results are illustrated.