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Wavelet based outlier correction for power controlled turning point detection in surveillance systems Economic Modelling

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Author

  • Yushu Li

Summary, in English

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.

Publishing year

2013

Language

English

Pages

317-321

Publication/Series

Economic Modelling

Volume

30

Document type

Journal article

Publisher

Elsevier, Elsevier

Topic

  • Economics

Keywords

  • Unimodel
  • Turning point
  • Statistical surveillance
  • Outlier
  • Wavelet multi-resolution
  • Threshold.

Status

Published

ISBN/ISSN/Other

  • ISSN: 0264-9993