Finite-time sampled-data synchronization for uncertain neutral-type semi-Markovian jump neural networks with mixed time-varying delays

Yao Wang, Jun Guo, Guobao Liu, Junwei Lu and Fangyuan Li

Applied Mathematics and Computation, 2021, vol. 403, issue C

Abstract: This paper addresses the finite-time synchronization problem for neutral-type semi-Markovian jump neural networks subject to random occurred uncertainties by sampled-data control approach. In order to deal with the influence of leakage delay and additive time delays on neutral-type neural networks, an appropriate Lyapunov–Krasovskii functional is employed. Some sufficient conditions are presented to guarantee the stochastic finite-time synchronization of the master system and slave system with an L2−L∞ performance level. In terms of linear matrix inequalities, the sampled-data controller gains are obtained. Two numerical examples are provided to demonstrate the effectiveness of our proposed method.

Keywords: Finite-time analysis; Semi-Markovian jump; Sampled-data control; Synchronization; Neutral-type neural networks; Mixed time delays (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:403:y:2021:i:c:s0096300321002873

DOI: 10.1016/j.amc.2021.126197

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