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

Yushu Li

CREATES Research Papers from Department of Economics and Business Economics, Aarhus University

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 C15 C22 (search for similar items in EconPapers)
Pages: 18
Date: 2011-07-15
New Economics Papers: this item is included in nep-ecm and nep-ets
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https://repec.econ.au.dk/repec/creates/rp/11/rp11_29.pdf (application/pdf)

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 (2012)
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Persistent link: https://EconPapers.repec.org/RePEc:aah:create:2011-29

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