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Applied Optics

Applied Optics


  • Editor: Glenn D. Boreman
  • Vol. 44, Iss. 33 — Nov. 20, 2005
  • pp: 7091–7097

Least-squares support vector machines modelization for time-resolved spectroscopy

Fabien Chauchard, Sylvie Roussel, Jean-Michel Roger, Véronique Bellon-Maurel, Christoffer Abrahamsson, Tomas Svensson, Stefan Andersson-Engels, and Sune Svanberg  »View Author Affiliations

Applied Optics, Vol. 44, Issue 33, pp. 7091-7097 (2005)

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By use of time-resolved spectroscopy it is possible to separate light scattering effects from chemical absorption effects in samples. In the study of propagation of short light pulses in turbid samples the reduced scattering coefficient and the absorption coefficient are usually obtained by fitting diffusion or Monte Carlo models to the measured data by use of numerical optimization techniques. In this study we propose a prediction model obtained with a semiparametric modeling technique: the least-squares support vector machines. The main advantage of this technique is that it uses theoretical time dispersion curves during the calibration step. Predictions can then be performed by use of data measured on different kinds of sample, such as apples.

© 2005 Optical Society of America

OCIS Codes
(000.3860) General : Mathematical methods in physics
(170.3660) Medical optics and biotechnology : Light propagation in tissues
(290.7050) Scattering : Turbid media
(300.6500) Spectroscopy : Spectroscopy, time-resolved

ToC Category:

Original Manuscript: February 28, 2005
Revised Manuscript: May 10, 2005
Manuscript Accepted: May 16, 2005
Published: November 20, 2005

Fabien Chauchard, Sylvie Roussel, Jean-Michel Roger, Véronique Bellon-Maurel, Christoffer Abrahamsson, Tomas Svensson, Stefan Andersson-Engels, and Sune Svanberg, "Least-squares support vector machines modelization for time-resolved spectroscopy," Appl. Opt. 44, 7091-7097 (2005)

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