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

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摘要

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.

论文关键词:Discrete-time recurrent neural network,Sliding mode control,Quantized method,Synchronization

论文评审过程:Received 13 August 2019, Revised 12 January 2020, Accepted 25 January 2020, Available online 17 February 2020, Version of Record 17 February 2020.

论文官网地址:https://doi.org/10.1016/j.amc.2020.125093