Combination of Wavelet Multiscale Analysis and Support Vector Machines for Determination of Multicomponent

This paper suggests a novel method named DF-LS-SVM based on least squares support vector machines (LS-SVM) regression combine with multiscale wavelet transforms and data fusion (DF) to enhance the ability to extract characteristic information and improve the quality of the regression. Experimental results showed the DF-LS-SVM method was successful for simultaneous multicomponent determination even where there was severe overlap of spectra. The DF-LS-SVM method is a hybrid technique that combines the best properties of the two techniques and makes this method attractive and promising.