Weighted LS-SVM for function estimation applied to artifact removal in bio-signal processing

Alexander Caicedo, Sabine Van Huffel

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

12 Scopus citations

Abstract

Weighted LS-SVM is normally used for function estimation from highly corrupted data in order to decrease the impact of outliers. However, this method is limited in size and big time series should be segmented in smaller groups. Therefore, border discontinuities represent a problem in the final estimated function. Several methods such as committee networks or multilayer networks of LS-SVMs are used to address this problem, but these methods require extra training and hence the computational cost is increased. In this paper a technique that includes an extra weight vector in the formulation of the cost function for the LS-SVM problem is proposed as an alternative solution. The method is then applied to the removal of some artifacts in biomedical signals.

Original languageEnglish (US)
Title of host publication2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
Pages988-991
Number of pages4
DOIs
StatePublished - 2010
Externally publishedYes
Event2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 - Buenos Aires, Argentina
Duration: Aug 31 2010Sep 4 2010

Publication series

Name2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10

Conference

Conference2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
CountryArgentina
CityBuenos Aires
Period8/31/109/4/10

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Health Informatics

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