Wavelet Based Outlier Correction for Power Controlled Turning Point Detection in Surveillance Systems

Yushu Li

No 2012:12, Working Papers from Lund University, Department of Economics

Abstract: Detection turning points in unimodel has various applications to time series which have cyclic periods. Related techniques are widely explored in the field of statistical surveillance, that is, on-line turning point detection procedures. This paper will first present a power controlled turning point detection method based on the theory of the likelihood ratio test in statistical surveillance. Next we show how outliers will influence the performance of this methodology. Due to the sensitivity of the surveillance system to outliers, we finally present a wavelet multiresolution (MRA) based outlier elimination approach, which can be combined with the on-line turning point detection process and will then alleviate the false alarm problem introduced by the outliers.

Keywords: Unimodel; Turning point; Statistical Surveillance; Outlier; Wavelet multiresolution; Threshold (search for similar items in EconPapers)
JEL-codes: C12 C52 C63 (search for similar items in EconPapers)
Pages: 15 pages
Date: 2012-05-21
New Economics Papers: this item is included in nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://lucris.lub.lu.se/ws/portalfiles/portal/194823944/WP12_12 Full text (application/pdf)
Our link check indicates that this URL is bad, the error code is: 404 404

Related works:
Journal Article: Wavelet based outlier correction for power controlled turning point detection in surveillance systems (2013)
Working Paper: Wavelet Based Outlier Correction for Power Controlled Turning Point Detection in Surveillance Systems (2011)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hhs:lunewp:2012_012

Access Statistics for this paper

More papers in Working Papers from Lund University, Department of Economics School of Economics and Management, Box 7080, S-22007 Lund, Sweden. Contact information at EDIRC.
Bibliographic data for series maintained by Iker Arregui Alegria ().