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

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 t...

Full description

Saved in:
Bibliographic Details
Published in:Neural processing letters 2023-06, Vol.55 (3), p.2965-2987
Main Authors: Hong, Mengting, Ren, Fengli, Yang, Yong
Format: Article
Language:English
Subjects:
Artificial Intelligence
Brownian motion
Complex Systems
Computational Intelligence
Computer Science
Feedback control
Graph theory
Markov analysis
Markov chains
Martingales
Networks
Random variables
State feedback
Stochastic processes
Synchronism
Time lag
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:1370-4621
1573-773X
DOI:10.1007/s11063-022-10993-5