期刊
APPLIED MATHEMATICS AND COMPUTATION
卷 375, 期 -, 页码 -出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.amc.2020.125093
关键词
Discrete-time recurrent neural network; Sliding mode control; Quantized method; Synchronization
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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