Least-squares support vector machines modelization for time-resolved spectroscopy
Författare
Summary, in English
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.
Avdelning/ar
Publiceringsår
2005
Språk
Engelska
Sidor
7091-7097
Publikation/Tidskrift/Serie
Applied Optics
Volym
44
Issue
33
Fulltext
Länkar
Dokumenttyp
Artikel i tidskrift
Förlag
Optical Society of America
Ämne
- Atom and Molecular Physics and Optics
Status
Published
ISBN/ISSN/Övrigt
- ISSN: 2155-3165