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

Alexander Caicedo, Sabine Van Huffel

Producción: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

12 Citas (Scopus)

Resumen

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.

Idioma originalInglés
Título de la publicación alojada2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
Páginas988-991
Número de páginas4
DOI
EstadoPublicada - 2010
Publicado de forma externa
Evento2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 - Buenos Aires, Argentina
Duración: 31 ago. 201004 sep. 2010

Serie de la publicación

Nombre2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10

Conferencia

Conferencia2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
País/TerritorioArgentina
CiudadBuenos Aires
Período31/08/1004/09/10

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