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Stochastic synchronization for semi-Markovian complex dynamic networks with partly unknown transition rates.
- Source :
-
Neurocomputing . Apr2023, Vol. 528, p59-74. 16p. - Publication Year :
- 2023
-
Abstract
- This paper investigates the synchronization of complex dynamic networks with time-varying delay and general semi-Markovian jump. The general transition rates include completely unknown and uncertain but bounded as two special cases. First, by introducing auxiliary vectors with a few nonorthogonal polynomials, two free-matrix-based integral inequalities are developed, which encompass some existing ones as special cases. Second, an integral- based delay-product-type Lyapunov-Krasovskii functional is constructed, which fully considers the information of time delay. By utilizing a deley-dependent controller, two sufficient conditions are derived to realize the global stochastic mean-square synchronization by employing the established inequalities to evaluate the infinitesimal generator of the functional. This paper takes all possibilities into consideration and divides the general transition rates into five cases, which is never investigated before. Finally a numerical example is given to show the effectiveness and practicality of the presented method. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09252312
- Volume :
- 528
- Database :
- Academic Search Index
- Journal :
- Neurocomputing
- Publication Type :
- Academic Journal
- Accession number :
- 161903368
- Full Text :
- https://doi.org/10.1016/j.neucom.2023.01.019