4.7 Article

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

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APPLIED MATHEMATICS AND COMPUTATION
卷 375, 期 -, 页码 -

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ELSEVIER SCIENCE INC
DOI: 10.1016/j.amc.2020.125093

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Discrete-time recurrent neural network; Sliding mode control; Quantized method; Synchronization

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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. (C) 2020 Elsevier Inc. All rights reserved.

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