A fuzzy classification system for analysis of polymer spectra using fast wavelet transforms
G. Wirth, C.F. Bale, D.A. Mlynski · 2002
We propose an efficient strategy for qualitative analysis of measured polymer spectra based on fast wavelet transforms and fuzzy set theory. First a wavelet transform is applied to the measured data acting as a feature extractor. Thus huge data sets are enormously compressed and only a few typical features (wavelet coefficients) locating the spectra peaks remain for the identification process. Then, a fuzzy classification algorithm separates different spectra into various clusters thus giving a qualitative interpretation of the ingredients due to calculated membership values. For that we implemented a fuzzy c-means algorithm, a fuzzy Kohonen cluster algorithm and special rule based approach with fuzzy if-then rules.