Synchronization of discrete-time recurrent neural networks with time-varying delays via quantized sliding mode control

Bo Sun, Yuting Cao, Zhenyuan Guo, Zheng Yan and Shiping Wen

Applied Mathematics and Computation, 2020, vol. 375, issue C

Abstract: In this paper, we discuss synchronization of discrete-time recurrent neural networks (DRNNs) with time-varying delays via quantized sliding mode control. A feedback controller based on sliding mode control is firstly imported in the synchronization of DRNNs. The activation functional in our paper can be more relaxed than the other papers which should satisfy the Lipschitz conditions. For the sake of reducing the computational complexity and conservatism, we consider two quantized methods with uniform and logarithmic quantizer. We gain some specific conditions to ensure the synchronization of discrete-time system. Several examples are presented to support our theorem in the ending.

Keywords: Discrete-time recurrent neural network; Sliding mode control; Quantized method; Synchronization (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:375:y:2020:i:c:s009630032030062x

DOI: 10.1016/j.amc.2020.125093

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