Robust Stabilization of Delayed Neural Networks: Dissipativity-Learning Approach

Robust Stabilization of Delayed Neural Networks: Dissipativity-Learning Approach

© 2012 IEEE. This paper examines the robust stabilization problem of continuous-time delayed neural networks via the dissipativity-learning approach. A new learning algorithm is established to guarantee the asymptotic stability as well as the (Q,S,R) - α -dissipativity of the considered neural netw...

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Main Authors: Ramasamy Saravanakumar, Hyung Soo Kang, Choon Ki Ahn, Xiaojie Su, Hamid Reza Karimi
Other Authors: Chongqing University
Format: Article
Published: 2020
Subjects:
Computer Science
Online Access:https://repository.li.mahidol.ac.th/handle/123456789/50642
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spelling th-mahidol.506422020-01-27T15:20:55Z Robust Stabilization of Delayed Neural Networks: Dissipativity-Learning Approach Ramasamy Saravanakumar Hyung Soo Kang Choon Ki Ahn Xiaojie Su Hamid Reza Karimi Chongqing University Politecnico di Milano Mahidol University Kunsan National University Korea University Computer Science © 2012 IEEE. This paper examines the robust stabilization problem of continuous-time delayed neural networks via the dissipativity-learning approach. A new learning algorithm is established to guarantee the asymptotic stability as well as the (Q,S,R) - α -dissipativity of the considered neural networks. The developed result encompasses some existing results, such as H ∞ and passivity performances, in a unified framework. With the introduction of a Lyapunov-Krasovskii functional together with the Legendre polynomial, a novel delay-dependent linear matrix inequality (LMI) condition and a learning algorithm for robust stabilization are presented. Demonstrative examples are given to show the usefulness of the established learning algorithm. 2020-01-27T08:20:55Z 2020-01-27T08:20:55Z 2019-03-01 Article IEEE Transactions on Neural Networks and Learning Systems. Vol.30, No.3 (2019), 913-922 10.1109/TNNLS.2018.2852807 21622388 2162237X 2-s2.0-85050997468 https://repository.li.mahidol.ac.th/handle/123456789/50642 Mahidol University SCOPUS https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85050997468&origin=inward
institution Mahidol University
building Mahidol University Library
continent Asia
country Thailand
Thailand
content_provider Mahidol University Library
collection Mahidol University Institutional Repository
topic Computer Science
spellingShingle Computer Science
Ramasamy Saravanakumar
Hyung Soo Kang
Choon Ki Ahn
Xiaojie Su
Hamid Reza Karimi
Robust Stabilization of Delayed Neural Networks: Dissipativity-Learning Approach
description © 2012 IEEE. This paper examines the robust stabilization problem of continuous-time delayed neural networks via the dissipativity-learning approach. A new learning algorithm is established to guarantee the asymptotic stability as well as the (Q,S,R) - α -dissipativity of the considered neural networks. The developed result encompasses some existing results, such as H ∞ and passivity performances, in a unified framework. With the introduction of a Lyapunov-Krasovskii functional together with the Legendre polynomial, a novel delay-dependent linear matrix inequality (LMI) condition and a learning algorithm for robust stabilization are presented. Demonstrative examples are given to show the usefulness of the established learning algorithm.
author2 Chongqing University
author_facet Chongqing University
Ramasamy Saravanakumar
Hyung Soo Kang
Choon Ki Ahn
Xiaojie Su
Hamid Reza Karimi
format Article
author Ramasamy Saravanakumar
Hyung Soo Kang
Choon Ki Ahn
Xiaojie Su
Hamid Reza Karimi
author_sort Ramasamy Saravanakumar
title Robust Stabilization of Delayed Neural Networks: Dissipativity-Learning Approach
title_short Robust Stabilization of Delayed Neural Networks: Dissipativity-Learning Approach
title_full Robust Stabilization of Delayed Neural Networks: Dissipativity-Learning Approach
title_fullStr Robust Stabilization of Delayed Neural Networks: Dissipativity-Learning Approach
title_full_unstemmed Robust Stabilization of Delayed Neural Networks: Dissipativity-Learning Approach
title_sort robust stabilization of delayed neural networks: dissipativity-learning approach
publishDate 2020
url https://repository.li.mahidol.ac.th/handle/123456789/50642
_version_ 1763489532111486976

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