Comparison of three algorithms for parametric change-point detection

Cynthia Faure; Jean Marc Bardet; Madalina Olteanu; Jéroôme Lacaille

Comparison of three algorithms for parametric change-point detection

Cynthia Faure, Jean Marc Bardet, Madalina Olteanu, Jéroôme Lacaille

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

Abstract

Numerous sensors placed on aircraft engines capture a considerable amount of data during tests or ights. In order to detect potential crucial changes of characteristic features, it is relevant to develop powerful statistical algorithms. This manuscript aims at detecting change-points, in an off-line framework, in piecewise-linear models and with an unknown number of change-points. In this context, three recent algorithms are considered, implemented and compared on simulated and real data.

Original language	English
Title of host publication	ESANN 2016 - 24th European Symposium on Artificial Neural Networks
Publisher	i6doc.com publication
Pages	89-94
Number of pages	6
ISBN (Electronic)	9782875870278
Publication status	Published - 1 Jan 2016
Externally published	Yes
Event	24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2016 - Bruges, Belgium Duration: 27 Apr 2016 → 29 Apr 2016

Publication series

Name	ESANN 2016 - 24th European Symposium on Artificial Neural Networks

Conference

Conference	24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2016
Country/Territory	Belgium
City	Bruges
Period	27/04/16 → 29/04/16

Cite this

@inproceedings{a19ed1e4fb3146019dde9d8ca141cc4d,

title = "Comparison of three algorithms for parametric change-point detection",

abstract = "Numerous sensors placed on aircraft engines capture a considerable amount of data during tests or ights. In order to detect potential crucial changes of characteristic features, it is relevant to develop powerful statistical algorithms. This manuscript aims at detecting change-points, in an off-line framework, in piecewise-linear models and with an unknown number of change-points. In this context, three recent algorithms are considered, implemented and compared on simulated and real data.",

author = "Cynthia Faure and Bardet, \{Jean Marc\} and Madalina Olteanu and J{\'e}ro{\^o}me Lacaille",

year = "2016",

month = jan,

day = "1",

language = "English",

series = "ESANN 2016 - 24th European Symposium on Artificial Neural Networks",

publisher = "i6doc.com publication",

pages = "89--94",

booktitle = "ESANN 2016 - 24th European Symposium on Artificial Neural Networks",

note = "24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2016 ; Conference date: 27-04-2016 Through 29-04-2016",

}

Faure, C, Bardet, JM, Olteanu, M & Lacaille, J 2016, Comparison of three algorithms for parametric change-point detection. in ESANN 2016 - 24th European Symposium on Artificial Neural Networks. ESANN 2016 - 24th European Symposium on Artificial Neural Networks, i6doc.com publication, pp. 89-94, 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2016, Bruges, Belgium, 27/04/16.

Comparison of three algorithms for parametric change-point detection. / Faure, Cynthia; Bardet, Jean Marc; Olteanu, Madalina et al.
ESANN 2016 - 24th European Symposium on Artificial Neural Networks. i6doc.com publication, 2016. p. 89-94 (ESANN 2016 - 24th European Symposium on Artificial Neural Networks).

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

TY - GEN

T1 - Comparison of three algorithms for parametric change-point detection

AU - Faure, Cynthia

AU - Bardet, Jean Marc

AU - Olteanu, Madalina

AU - Lacaille, Jéroôme

PY - 2016/1/1

Y1 - 2016/1/1

N2 - Numerous sensors placed on aircraft engines capture a considerable amount of data during tests or ights. In order to detect potential crucial changes of characteristic features, it is relevant to develop powerful statistical algorithms. This manuscript aims at detecting change-points, in an off-line framework, in piecewise-linear models and with an unknown number of change-points. In this context, three recent algorithms are considered, implemented and compared on simulated and real data.

AB - Numerous sensors placed on aircraft engines capture a considerable amount of data during tests or ights. In order to detect potential crucial changes of characteristic features, it is relevant to develop powerful statistical algorithms. This manuscript aims at detecting change-points, in an off-line framework, in piecewise-linear models and with an unknown number of change-points. In this context, three recent algorithms are considered, implemented and compared on simulated and real data.

M3 - Conference contribution

AN - SCOPUS:84994136070

T3 - ESANN 2016 - 24th European Symposium on Artificial Neural Networks

SP - 89

EP - 94

BT - ESANN 2016 - 24th European Symposium on Artificial Neural Networks

PB - i6doc.com publication

T2 - 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2016

Y2 - 27 April 2016 through 29 April 2016

ER -

Comparison of three algorithms for parametric change-point detection

Abstract

Publication series

Conference

Fingerprint

Cite this