State estimation of memristor-based recurrent neural networks with time-varying delays based on passivity theory-Reference-Cited by-同舟云学术

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State estimation of memristor-based recurrent neural networks with time-varying delays based on passivity theory

Published:2013-11-12 Issue:4 Volume:19 Page:32-43
ISSN:1076-2787
Container-title:Complexity
language:en
Short-container-title:Complexity

Author:

Rakkiyappan R.¹,Chandrasekar A.¹,Laksmanan S.²,Park Ju H.³

Affiliation:

1. Department of Mathematics; Bharathiar University; Coimbatore 641 046 Tamil Nadu India

2. Department of Mathematical Sciences; College of Science, UAE University; Al Ain 15551 UAE

3. Department of Electrical Engineering; Yeungnam University; 214-1 Dae-Dong Kyongsan 712-749 Republic of Korea

Publisher

Wiley

Subject

Multidisciplinary,General Computer Science

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/cplx.21482/fullpdf

Reference40 articles.

1. An analysis of global asymptotic stability of delayed cellular neural networks;Arik;IEEE Trans Neural Netw,2002

2. On learning of sigmoid neural networks;Najarian;Complexity,2001

3. How neutral networks influence evolvability;Ebner;Complexity,2002

4. How to train a neural network: An introduction to the new computational paradigm;Johnson;Complexity,1996

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