Sampled-data control for state estimation of static neural networks

H. Y. Jung; J. H. Park; S. M. Lee

doi:10.1109/CSCI.2014.144

Sampled-data control for state estimation of static neural networks

H. Y. Jung, J. H. Park, S. M. Lee

School of Electronics Engineering

Yeungnam University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

In this brief, the problem of sampled-data state estimation for static neural network is investigated. The statefeedback control design method we develop in this paper relies on the information from the sampled states. By constructing a class of Lyapunov function and combining with some inequality, a sufficient condition for the existence of state estimator is derived.

Original language	English
Title of host publication	Proceedings - 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014
Publisher	IEEE Computer Society
Pages	301-302
Number of pages	2
ISBN (Print)	9781479930098
DOIs	https://doi.org/10.1109/CSCI.2014.144
State	Published - 2014
Event	2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014 - Las Vegas, NV, United States Duration: 10 Mar 2014 → 13 Mar 2014

Publication series

Name	Proceedings - 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014
Volume	2

Conference

Conference	2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014
Country/Territory	United States
City	Las Vegas, NV
Period	10/03/14 → 13/03/14

Keywords

Neural networks
Sampled-data
State estimation

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10.1109/CSCI.2014.144

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Jung, H. Y., Park, J. H., & Lee, S. M. (2014). Sampled-data control for state estimation of static neural networks. In Proceedings - 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014 (pp. 301-302). Article 6822355 (Proceedings - 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014; Vol. 2). IEEE Computer Society. https://doi.org/10.1109/CSCI.2014.144

Jung, H. Y. ; Park, J. H. ; Lee, S. M. / Sampled-data control for state estimation of static neural networks. Proceedings - 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014. IEEE Computer Society, 2014. pp. 301-302 (Proceedings - 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014).

@inproceedings{667536d832134af9b26af245167699fa,

title = "Sampled-data control for state estimation of static neural networks",

abstract = "In this brief, the problem of sampled-data state estimation for static neural network is investigated. The statefeedback control design method we develop in this paper relies on the information from the sampled states. By constructing a class of Lyapunov function and combining with some inequality, a sufficient condition for the existence of state estimator is derived.",

keywords = "Neural networks, Sampled-data, State estimation",

author = "Jung, {H. Y.} and Park, {J. H.} and Lee, {S. M.}",

year = "2014",

doi = "10.1109/CSCI.2014.144",

language = "English",

isbn = "9781479930098",

series = "Proceedings - 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014",

publisher = "IEEE Computer Society",

pages = "301--302",

booktitle = "Proceedings - 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014",

address = "United States",

note = "2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014 ; Conference date: 10-03-2014 Through 13-03-2014",

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Jung, HY, Park, JH & Lee, SM 2014, Sampled-data control for state estimation of static neural networks. in Proceedings - 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014., 6822355, Proceedings - 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014, vol. 2, IEEE Computer Society, pp. 301-302, 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014, Las Vegas, NV, United States, 10/03/14. https://doi.org/10.1109/CSCI.2014.144

Sampled-data control for state estimation of static neural networks. / Jung, H. Y.; Park, J. H.; Lee, S. M.
Proceedings - 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014. IEEE Computer Society, 2014. p. 301-302 6822355 (Proceedings - 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014; Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - In this brief, the problem of sampled-data state estimation for static neural network is investigated. The statefeedback control design method we develop in this paper relies on the information from the sampled states. By constructing a class of Lyapunov function and combining with some inequality, a sufficient condition for the existence of state estimator is derived.

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Y2 - 10 March 2014 through 13 March 2014

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Jung HY, Park JH, Lee SM. Sampled-data control for state estimation of static neural networks. In Proceedings - 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014. IEEE Computer Society. 2014. p. 301-302. 6822355. (Proceedings - 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014). doi: 10.1109/CSCI.2014.144

Sampled-data control for state estimation of static neural networks

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