4.5 Article

Decentralized Event-Triggered Exponential Stability for Uncertain Delayed Genetic Regulatory Networks with Markov Jump Parameters and Distributed Delays

Journal

NEURAL PROCESSING LETTERS
Volume 47, Issue 3, Pages 1219-1252

Publisher

SPRINGER
DOI: 10.1007/s11063-017-9695-2

Keywords

Event-triggered; Genetic regulatory networks (GRNs); Markovian jump parameters; Lyapunov-Krasovskii functional; Linear matrix inequality

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This paper is concerned with the stability problem for a class of decentralized event-triggered exponential stability for uncertain delayed genetic regulatory networks (GRNs) with Markov jump parameters and distributed delays. In order to reduce the information communication burden, the decentralized event-triggered mechanism is proposed in this paper. Exponential stability for the proposed GRNs are studied by the Lyapunov method and the matrix inequality techniques. Some new sufficient conditions are obtained to ensure the global exponential stability of the proposed GRNs. Furthermore, the proposed LMI results are computationally efficient which are easy to be verified via the Matlab LMI toolbox. In addition, four numerical examples are provided to illustrate the effectiveness of the theoretical results.

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