Centralized/decentralized event-triggered pinning synchronization of stochastic coupled networks with noise and incomplete transitional rate.
Journal:
Neural networks : the official journal of the International Neural Network Society
Published Date:
Sep 7, 2019
Abstract
This paper studies the synchronous problem of Markovian switching complex networks associated with partly unknown transitional rates, stochastic noise, and randomly coupling strength. In order to achieve the synchronization for these array networks, event-triggered pinning control is established and developed, in which the pinning node undergoes a self-adapted switch, governed by a Markov chain. Two types of event-triggered sampling controls, centralized and decentralized event-triggered sampling, respectively, are established. Sufficient conditions for synchronization are developed by constructing a desirable stochastic Lyapunov functional as well as by employing the properties of Markov chain and Itoˆ integration. Numerical simulations are provided to demonstrate the effectiveness of the proposed approach.