Finite-time non-fragile control for synchronization of fractional-order stochastic neural networks

Abstract

This study concerned with the synchronization problem in finite-time domain for a class of fractional-order stochastic neural networks via non-fragile controller with discontinuous activation functions. Specifically, the suggested state feedback controller sequentially cope with non-fragile scheme for gain scheduling process. Notably, the main objective of this work is to develop a non-fragile controller to obtained the finite-time synchronization criterion for the resulting synchronized error system over finite bound. For that, some consignment of sufficient conditions is derived systematically by implementing Lyapunovs indirect method and finite-time stability theory which ensures the finite-time stochastic synchronization of the stipulated neural networks. Later on, the controller gain fluctuations that obeying certain white noise sequels derived from Bernoulli distribution are formulated in terms of linear matrix inequalities. Eventually, the illustrated study are substantiated through two numerical examples and the simulation results manifest the advantage and accuracy of the proposed synchronization criteria.

Power-exponential and fixed-time consensus of conformable fractional-order quantum cellular neural networks via event-triggered control

“…As an important dynamic behavior of chaotic systems, synchronization exists widely in application areas such as cryptographic construction systems, fault diagnosis systems, multiuser detection systems, and image watermarking systems [28][29][30][31][32][33][34][35][36][37]. During the past several years, various kinds of synchronization have been proposed in control science, such as asymptotic synchronization and finite-time synchronization.…”

Impulsive Destabilization Effect on Novel Existence of Solution and Global μ-Stability for MNNs in Quaternion Field

“…Among all the dynamical behaviors, stability and synchronization [32][33][34][35] are the most important properties. Therefore, as a generalization stability, µ-stability, including power and exponential stability, has attracted many scholars' attentions [30,31,36,37].…”