Sampled-data synchronization criteria for Markovian jumping neural networks with additive time-varying delays using new techniques

Tao Wu, Jinde Cao, Lianglin Xiong, Haiyang Zhang and Jinlong Shu

Applied Mathematics and Computation, 2022, vol. 413, issue C

Abstract: This paper investigates the sampled-data synchronization issue of Markovian jumping neural networks with additive time-varying delays. Firstly, a ternary quadratic function negative-determination condition and the bilateral sampled-interval-related Lyapunov functional (BSIRLF) approach are proposed. Based on the developed two novel approaches, some new criteria based on the linear matrix inequalities (LMIs) are established to guarantee the drive-response stochastic sampled-data synchronization of Markovian jumping neural networks with additive time-varying delays. Meanwhile, the corresponding sampled-data controller gains are designed under the larger sampling interval. In the end, the availability and merits of the developed approaches are displayed via two simulative examples.

Keywords: Markovian jumping neural networks; Additive time-varying delays; Sampled-data control; Synchronization (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:413:y:2022:i:c:s0096300321006883

DOI: 10.1016/j.amc.2021.126604

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