Finite-time synchronization control for semi-Markov jump neural networks with mode-dependent stochastic parametric uncertainties

Dian Zhang, Jun Cheng, Jinde Cao and Dan Zhang

Applied Mathematics and Computation, 2019, vol. 344-345, 230-242

Abstract: This paper addresses the problem of synchronization control for semi-Markov jump neural networks with mode-dependent stochastic parametric uncertainties covering a finite-time period. A more general semi-Markov jump neural network is developed by the mode-dependent stochastic parametric uncertainties technique, where both upper and lower bounds of parametric uncertainties are taken into consideration in determining the imprecise measurements. The time-varying semi-Markov chain information subject to uncertainty is established, and sufficient conditions are achieved combine with some integral method. Finally, two numerical examples are exhibited to verify the effectiveness of the produced scheme.

Keywords: Semi-Markov chain; Markov jump neural network; Unreliable communication link; Parametric uncertainty; Finite-time synchronization (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:344-345:y:2019:i::p:230-242

DOI: 10.1016/j.amc.2018.09.013

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