International Journal of Computational Intelligence Systems

Volume 4, Issue 5, September 2011, Pages 855 - 862

H-infinite State Estimation for Takagi-Sugeno Fuzzy Delayed Hopfield Neural Networks

Authors
Choon Ki Ahn
Corresponding Author
Choon Ki Ahn
Received 19 April 2010, Accepted 17 June 2011, Available Online 1 September 2011.
DOI
10.2991/ijcis.2011.4.5.11How to use a DOI?
Keywords
H-infinite state estimation, Takagi-Sugeno fuzzy Hopfield neural networks, linear matrix inequality
Abstract

This paper presents a H-infinite state estimator for Takagi-Sugeno fuzzy delayed Hopfield neural networks. Based on Lyapunov-Krasovskii stability approach, a delay-dependent criterion is proposed to ensure that the resulting estimation error system is asymptotically stable with a guaranteed H performance. The proposed H state estimator can be realized by solving a linear matrix inequality (LMI) problem. An illustrative numerical example is given to verify the effectiveness of the proposed H-infinite state estimator.

Copyright
© 2011, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
4 - 5
Pages
855 - 862
Publication Date
2011/09/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.2011.4.5.11How to use a DOI?
Copyright
© 2011, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Choon Ki Ahn
PY  - 2011
DA  - 2011/09/01
TI  - H-infinite State Estimation for Takagi-Sugeno Fuzzy Delayed Hopfield Neural Networks
JO  - International Journal of Computational Intelligence Systems
SP  - 855
EP  - 862
VL  - 4
IS  - 5
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2011.4.5.11
DO  - 10.2991/ijcis.2011.4.5.11
ID  - KiAhn2011
ER  -