Passivity analysis of memristor-based recurrent neural networks with time-varying delays
Publication
, Journal Article
Wen, S; Zeng, Z; Huang, T; Chen, Y
Published in: Journal of the Franklin Institute
October 1, 2013
This paper investigates the delay-dependent exponential passivity problem of the memristor-based recurrent neural networks (RNNs). Based on the knowledge of memristor and recurrent neural network, the model of the memristor-based RNNs is established. Taking into account of the information of the neuron activation functions and the involved time-varying delays, several improved results with less computational burden and conservatism have been obtained in the sense of Filippov solutions. A numerical example is presented to show the effectiveness of the obtained results. © 2013 The Franklin Institute.
Duke Scholars
Published In
Journal of the Franklin Institute
DOI
ISSN
0016-0032
Publication Date
October 1, 2013
Volume
350
Issue
8
Start / End Page
2354 / 2370
Related Subject Headings
- Industrial Engineering & Automation
- 4901 Applied mathematics
- 4006 Communications engineering
- 0906 Electrical and Electronic Engineering
- 0102 Applied Mathematics
Citation
APA
Chicago
ICMJE
MLA
NLM
Wen, S., Zeng, Z., Huang, T., & Chen, Y. (2013). Passivity analysis of memristor-based recurrent neural networks with time-varying delays. Journal of the Franklin Institute, 350(8), 2354–2370. https://doi.org/10.1016/j.jfranklin.2013.05.026
Wen, S., Z. Zeng, T. Huang, and Y. Chen. “Passivity analysis of memristor-based recurrent neural networks with time-varying delays.” Journal of the Franklin Institute 350, no. 8 (October 1, 2013): 2354–70. https://doi.org/10.1016/j.jfranklin.2013.05.026.
Wen S, Zeng Z, Huang T, Chen Y. Passivity analysis of memristor-based recurrent neural networks with time-varying delays. Journal of the Franklin Institute. 2013 Oct 1;350(8):2354–70.
Wen, S., et al. “Passivity analysis of memristor-based recurrent neural networks with time-varying delays.” Journal of the Franklin Institute, vol. 350, no. 8, Oct. 2013, pp. 2354–70. Scopus, doi:10.1016/j.jfranklin.2013.05.026.
Wen S, Zeng Z, Huang T, Chen Y. Passivity analysis of memristor-based recurrent neural networks with time-varying delays. Journal of the Franklin Institute. 2013 Oct 1;350(8):2354–2370.
Published In
Journal of the Franklin Institute
DOI
ISSN
0016-0032
Publication Date
October 1, 2013
Volume
350
Issue
8
Start / End Page
2354 / 2370
Related Subject Headings
- Industrial Engineering & Automation
- 4901 Applied mathematics
- 4006 Communications engineering
- 0906 Electrical and Electronic Engineering
- 0102 Applied Mathematics