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Synchronization of Complex Dynamical Networks Subject to Noisy Sampling Interval and Packet Loss

Zhipei Hu, Hongru Ren, Peng Shi

2021IEEE Transactions on Neural Networks and Learning Systems47 citationsDOI

Abstract

This article focuses on the sampled-data synchronization issue for a class of complex dynamical networks (CDNs) subject to noisy sampling intervals and successive packet losses. The sampling intervals are subject to noisy perturbations, and categorical distribution is used to characterize the sampling errors of noisy sampling intervals. By means of the input delay approach, the CDN under consideration is first converted into a delay system with delayed input subject to dual randomness and probability distribution characteristic. To verify the probability distribution characteristic of the delayed input, a novel characterization method is proposed, which is not the same as that of some existing literature. Based on this, a unified framework is then established. By recurring to the techniques of stochastic analysis, a probability-distribution-dependent controller is designed to guarantee the mean-square exponential synchronization of the error dynamical network. Subsequently, a special model is considered where only the lower and upper bounds of delayed input are utilized. Finally, to verify the analysis results and testify the effectiveness and superiority of the designed synchronization algorithm, a numerical example and an example using Chua's circuit are given.

Topics & Concepts

Synchronization (alternating current)Sampling (signal processing)Computer scienceRandomnessInterval (graph theory)AlgorithmMathematicsControl theory (sociology)StatisticsArtificial intelligenceControl (management)Filter (signal processing)Channel (broadcasting)Computer visionCombinatoricsComputer networkNeural Networks Stability and SynchronizationNonlinear Dynamics and Pattern FormationGene Regulatory Network Analysis