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15.08.2022

Synchronization of Stochastic Multi-Weights Complex Networks with Lévy Noise and Markovian Switching

verfasst von: Mengting Hong, Fengli Ren, Yong Yang

Erschienen in: Neural Processing Letters

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Abstract

This paper focuses on the synchronization issues of stochastic multi-weights complex networks associated with Lévy noise and Markov chains (SMWCNLM). Firstly, a synchronization criterion is obtained for the complex networks without the noisy time delay using the Lyapunov stability method and graph theory. Secondly, a sufficient condition is established to guarantee almost sure synchronization of the complex networks with the noisy time delay based on the non-negative semi-martingales convergence theorem in the framework of the stochastic process. Meanwhile, the coupling structure of all systems is controlled by continuous-time homogeneous Markov chains. To realize the synchronization of the systems, state feedback controllers are employed and these obtained synchronization principles are correlated to the multi-weights and the intensity of the noise. Finally, numerical simulations are presented to validate these theoretical results.
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Metadaten
Titel
Synchronization of Stochastic Multi-Weights Complex Networks with Lévy Noise and Markovian Switching
verfasst von
Mengting Hong
Fengli Ren
Yong Yang
Publikationsdatum
15.08.2022
Verlag
Springer US
Erschienen in
Neural Processing Letters
Print ISSN: 1370-4621
Elektronische ISSN: 1573-773X
DOI
https://doi.org/10.1007/s11063-022-10993-5