Analog circuit fault diagnosis based on DE-OS-ELM

Shaowei Chen; Minhua Wu; Shuai Zhao

doi:10.1109/ISCID.2014.94

Analog circuit fault diagnosis based on DE-OS-ELM

Shaowei Chen, Minhua Wu, Shuai Zhao

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

4 Citations (Scopus)

Abstract

Extreme Learning Machine has the quality of fast learning speed, good generalization performance, and high diagnostic accuracy. For analog circuit fault diagnosis and health management (PHM) applications, this paper presents the method of online sequential learning machine with differential evolution algorithm to optimize Extreme Learning Machine and improve the diagnostic accuracy and generalization performance effectively.

Original language	English
Title of host publication	Proceedings - 2014 7th International Symposium on Computational Intelligence and Design, ISCID 2014
Number of pages	5
Publisher	IEEE Signal Processing Society
Publication date	19 Mar 2015
Pages	509-513
Article number	7064245
ISBN (Electronic)	9781479970056
DOIs	https://doi.org/10.1109/ISCID.2014.94
Publication status	Published - 19 Mar 2015
Externally published	Yes
Event	7th International Symposium on Computational Intelligence and Design, ISCID 2014 - Hangzhou, China Duration: 13 Dec 2014 → 14 Dec 2014

Conference

Conference	7th International Symposium on Computational Intelligence and Design, ISCID 2014
Country/Territory	China
City	Hangzhou
Period	13/12/2014 → 14/12/2014
Sponsor	IEEE Nanjing Computational Intelligence Chapter, University of Bristol, Zhejiang Sci-Tech University, Zhejiang University

Series	Proceedings - 2014 7th International Symposium on Computational Intelligence and Design, ISCID 2014
Volume	1

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

analog circuits
differential evolution algorithm
online sequential learning machine

Access to Document

10.1109/ISCID.2014.94

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Cite this

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title = "Analog circuit fault diagnosis based on DE-OS-ELM",

abstract = "Extreme Learning Machine has the quality of fast learning speed, good generalization performance, and high diagnostic accuracy. For analog circuit fault diagnosis and health management (PHM) applications, this paper presents the method of online sequential learning machine with differential evolution algorithm to optimize Extreme Learning Machine and improve the diagnostic accuracy and generalization performance effectively.",

keywords = "analog circuits, differential evolution algorithm, online sequential learning machine",

author = "Shaowei Chen and Minhua Wu and Shuai Zhao",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 7th International Symposium on Computational Intelligence and Design, ISCID 2014 ; Conference date: 13-12-2014 Through 14-12-2014",

year = "2015",

month = mar,

day = "19",

doi = "10.1109/ISCID.2014.94",

language = "English",

series = "Proceedings - 2014 7th International Symposium on Computational Intelligence and Design, ISCID 2014",

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booktitle = "Proceedings - 2014 7th International Symposium on Computational Intelligence and Design, ISCID 2014",

publisher = "IEEE Signal Processing Society",

address = "United States",

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Chen, S, Wu, M & Zhao, S 2015, Analog circuit fault diagnosis based on DE-OS-ELM. in Proceedings - 2014 7th International Symposium on Computational Intelligence and Design, ISCID 2014., 7064245, IEEE Signal Processing Society, Proceedings - 2014 7th International Symposium on Computational Intelligence and Design, ISCID 2014, vol. 1, pp. 509-513, 7th International Symposium on Computational Intelligence and Design, ISCID 2014, Hangzhou, China, 13/12/2014. https://doi.org/10.1109/ISCID.2014.94

Analog circuit fault diagnosis based on DE-OS-ELM. / Chen, Shaowei; Wu, Minhua; Zhao, Shuai.
Proceedings - 2014 7th International Symposium on Computational Intelligence and Design, ISCID 2014. IEEE Signal Processing Society, 2015. p. 509-513 7064245 (Proceedings - 2014 7th International Symposium on Computational Intelligence and Design, ISCID 2014, Vol. 1).

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

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N2 - Extreme Learning Machine has the quality of fast learning speed, good generalization performance, and high diagnostic accuracy. For analog circuit fault diagnosis and health management (PHM) applications, this paper presents the method of online sequential learning machine with differential evolution algorithm to optimize Extreme Learning Machine and improve the diagnostic accuracy and generalization performance effectively.

AB - Extreme Learning Machine has the quality of fast learning speed, good generalization performance, and high diagnostic accuracy. For analog circuit fault diagnosis and health management (PHM) applications, this paper presents the method of online sequential learning machine with differential evolution algorithm to optimize Extreme Learning Machine and improve the diagnostic accuracy and generalization performance effectively.

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Chen S, Wu M, Zhao S. Analog circuit fault diagnosis based on DE-OS-ELM. In Proceedings - 2014 7th International Symposium on Computational Intelligence and Design, ISCID 2014. IEEE Signal Processing Society. 2015. p. 509-513. 7064245. (Proceedings - 2014 7th International Symposium on Computational Intelligence and Design, ISCID 2014, Vol. 1). doi: 10.1109/ISCID.2014.94

Analog circuit fault diagnosis based on DE-OS-ELM

Abstract

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Bibliographical note

Keywords

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