Stochastic exponential stabilization for Markov jump neural networks with time-varying delays via adaptive event-triggered impulsive control
type: Item
instance of: scholarly article
title: Stochastic exponential stabilization for Markov jump neural networks with time-varying delays via adaptive event-triggered impulsive control
zbMATH Open document ID: 1441.93325
DOI: 10.1155/2020/3956549
author: Xiaoman Liu
author: Haiyang Zhang
author: Tao Wu
author: Jinlong Shu
published in: Complexity
publication date: 2020-07-18T00:00:00Z
review text: Summary: This paper focuses on the exponential stabilization problem for Markov jump neural networks with Time-varying Delays (TDs). Firstly, we provide a new Free-matrix-based Exponential-type Integral Inequality (FMEII) containing the information of attenuation exponent, which is helpful to reduce the conservativeness of stability criteria. To further save control cost, we introduce a sample-based Adaptive Event-triggered Impulsive Control (AEIC) scheme, in which the trigger threshold is adaptively varied with the sampled state. By fully considering the information about sampled state, TDs, and Markov jump parameters, a suitable Lyapunov-Krasovskii functional is constructed. With the virtue of FMEII and AEIC scheme, some novel stabilization criteria are presented in the form of linear matrix inequalities. At last, two numerical examples are given to show the validity of the obtained results.
Mathematics Subject Classification ID: 93E15
Mathematics Subject Classification ID: 93A14
Mathematics Subject Classification ID: 92B20
zbMATH DE Number: 7222445
Wikidata QID: Q115521687
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2020/3956549
OpenAlex ID: W3038075506
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description: scientific article; zbMATH DE number 7222445