Title
Quantized passification of delayed memristor-based neural networks via sliding model control
Abstract
In this paper, quantized passification is investigated for memristive neural networks (MNNs) with time-varying delays via sliding model control. The controller is designed with quantized schemes to reduce the computational complexity via uniform quantization and logarithmic quantizer. By choosing suitable Lyapunov functional and using LMI toolbox, some specific conditions are obtained to make MNN passive. At last, we give an illustrative example to ensure the correctness of the theorem.
Year
DOI
Venue
2020
10.1016/j.jfranklin.2020.02.053
Journal of the Franklin Institute
DocType
Volume
Issue
Journal
357
6
ISSN
Citations 
PageRank 
0016-0032
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Bo Sun17020.66
yuting cao2489.75
Zhenyuan Guo345821.06
Zheng Yan4194.21
Shiping Wen5123172.34