Fixed-time synchronization of Markovian jump fuzzy cellular neural networks with stochastic disturbance and time-varying delays

This paper mainly studies the fixed-time synchronization of Markovian jump fuzzy cellular neural networks with stochastic perturbations, and time-varying delays in the leakage term. By designing delay-dependent controllers with or without fuzzy terms, constructing a suitable stochastic Lyapunov functional and using matrix analysis techniques, this paper derives some novel and useful sufficient conditions to guarantee the fixed-time synchronization of the addressed drive-response systems, and the conditions are delay-dependent, which has less conservative results. The finite time is also independent of the initial states. Finally, numerical examples are given to illustrate the effectiveness of the proposed main results. (c) 2020 Elsevier B.V. All rights reserved.

Automated summary

This paper investigates the fixed-time synchronization of Markovian jump fuzzy cellular neural networks with stochastic perturbations and time-varying delays. By designing delay-dependent controllers, constructing a suitable stochastic Lyapunov functional, and utilizing matrix analysis techniques, novel and useful sufficient conditions are derived to guarantee the synchronization in fixed time. The results are delay-dependent and less conservative, with finite time being independent of initial states.