A simple sequential outlier detection with several residuals

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Outlier detection schemes have been used to identify the unwanted noise and this helps us to obtain underlying valuable signals and predicting the next state of the systems/signals. However, there are few researches on sequential outlier detection in time series although a lot of outlier detection algorithms are developed in off-line systems. In this paper, we focus on the sequential (on-line) outlier detection schemes, that are based on the 'delete-replace' approach. We also demonstrate that three different types of residuals can be used to design the outlier detection scheme to achieve accurate sequential estimation: marginal residual, conditional residual, and contribution.

Original languageEnglish
Title of host publication2015 23rd European Signal Processing Conference, EUSIPCO 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2351-2355
Number of pages5
ISBN (Print)9780992862633
DOIs
Publication statusPublished - 2015 Dec 22
Event23rd European Signal Processing Conference, EUSIPCO 2015 - Nice, France
Duration: 2015 Aug 312015 Sep 4

Other

Other23rd European Signal Processing Conference, EUSIPCO 2015
CountryFrance
CityNice
Period15/8/3115/9/4

Fingerprint

Signal systems
Time series

Keywords

  • Conditional residual
  • Contribution
  • Marginal residual
  • Outlier detection

ASJC Scopus subject areas

  • Media Technology
  • Computer Vision and Pattern Recognition
  • Signal Processing

Cite this

Yoon, J. W. (2015). A simple sequential outlier detection with several residuals. In 2015 23rd European Signal Processing Conference, EUSIPCO 2015 (pp. 2351-2355). [7362805] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EUSIPCO.2015.7362805

A simple sequential outlier detection with several residuals. / Yoon, Ji Won.

2015 23rd European Signal Processing Conference, EUSIPCO 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 2351-2355 7362805.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Yoon, JW 2015, A simple sequential outlier detection with several residuals. in 2015 23rd European Signal Processing Conference, EUSIPCO 2015., 7362805, Institute of Electrical and Electronics Engineers Inc., pp. 2351-2355, 23rd European Signal Processing Conference, EUSIPCO 2015, Nice, France, 15/8/31. https://doi.org/10.1109/EUSIPCO.2015.7362805
Yoon JW. A simple sequential outlier detection with several residuals. In 2015 23rd European Signal Processing Conference, EUSIPCO 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 2351-2355. 7362805 https://doi.org/10.1109/EUSIPCO.2015.7362805
Yoon, Ji Won. / A simple sequential outlier detection with several residuals. 2015 23rd European Signal Processing Conference, EUSIPCO 2015. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 2351-2355
@inproceedings{af1d28f2217c41b88cb5728e096d23f4,
title = "A simple sequential outlier detection with several residuals",
abstract = "Outlier detection schemes have been used to identify the unwanted noise and this helps us to obtain underlying valuable signals and predicting the next state of the systems/signals. However, there are few researches on sequential outlier detection in time series although a lot of outlier detection algorithms are developed in off-line systems. In this paper, we focus on the sequential (on-line) outlier detection schemes, that are based on the 'delete-replace' approach. We also demonstrate that three different types of residuals can be used to design the outlier detection scheme to achieve accurate sequential estimation: marginal residual, conditional residual, and contribution.",
keywords = "Conditional residual, Contribution, Marginal residual, Outlier detection",
author = "Yoon, {Ji Won}",
year = "2015",
month = "12",
day = "22",
doi = "10.1109/EUSIPCO.2015.7362805",
language = "English",
isbn = "9780992862633",
pages = "2351--2355",
booktitle = "2015 23rd European Signal Processing Conference, EUSIPCO 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - A simple sequential outlier detection with several residuals

AU - Yoon, Ji Won

PY - 2015/12/22

Y1 - 2015/12/22

N2 - Outlier detection schemes have been used to identify the unwanted noise and this helps us to obtain underlying valuable signals and predicting the next state of the systems/signals. However, there are few researches on sequential outlier detection in time series although a lot of outlier detection algorithms are developed in off-line systems. In this paper, we focus on the sequential (on-line) outlier detection schemes, that are based on the 'delete-replace' approach. We also demonstrate that three different types of residuals can be used to design the outlier detection scheme to achieve accurate sequential estimation: marginal residual, conditional residual, and contribution.

AB - Outlier detection schemes have been used to identify the unwanted noise and this helps us to obtain underlying valuable signals and predicting the next state of the systems/signals. However, there are few researches on sequential outlier detection in time series although a lot of outlier detection algorithms are developed in off-line systems. In this paper, we focus on the sequential (on-line) outlier detection schemes, that are based on the 'delete-replace' approach. We also demonstrate that three different types of residuals can be used to design the outlier detection scheme to achieve accurate sequential estimation: marginal residual, conditional residual, and contribution.

KW - Conditional residual

KW - Contribution

KW - Marginal residual

KW - Outlier detection

UR - http://www.scopus.com/inward/record.url?scp=84963963390&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84963963390&partnerID=8YFLogxK

U2 - 10.1109/EUSIPCO.2015.7362805

DO - 10.1109/EUSIPCO.2015.7362805

M3 - Conference contribution

AN - SCOPUS:84963963390

SN - 9780992862633

SP - 2351

EP - 2355

BT - 2015 23rd European Signal Processing Conference, EUSIPCO 2015

PB - Institute of Electrical and Electronics Engineers Inc.

ER -