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Method for Artefact Detection and Suppression Using Alpha-Stable Distributions

  • Ludvík Tesař
  • Anthony Quinn
Conference paper

Abstract

This paper describes a method for artefact detection and suppression based on a-Stable distributions. The reason for choosing the a-stable distribution is, that it is heavy-tailed distribution ideal for modeling of data polluted by outliers. A method for on-line data processing is emphasized. The artefact suppression is based on the idea that data are modeled by a Symmetric α-Stable distribution, parameters of which are estimated. Then the data are regenerated from the Gaussian distribution with parameters, that correspond to the original parameters of the α-Stable distribution. The new data is free of any outliers.

Keywords

Weighted Median Impulsive Noise Cauchy Distribution Outlier Removal Artefact Detection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© Springer-Verlag Wien 2001

Authors and Affiliations

  • Ludvík Tesař
  • Anthony Quinn
    • 1
  1. 1.Trinity CollegeUniversity of DublinDublin 2Ireland

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