Data compression by a Fourier transform

Sets of spectroscopic data (IR, MS, NMR, UV-Vis) or other data are often subjected to one of the multivariate methods discussed in this book. One of the issues in this type of calculations is the reduction of the number variables by selecting a set of variables to be included in the data analysis. The opinion is gaining support that a selection of variables prior to the data analysis improves the results. For instance, variables which are little or not correlated to the property to be modeled are disregarded. Another approach is to compress all variables in a few features, e.g. by a principal components analysis (see Section 31.1). This is called 

Convolutes for the calculation of the smoothed second derivative (adapted from Ref. [8]) 

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Fig. 40.31. Data compression by a Fourier transform, (a) A spectrum measured at 512 wavelengths (b) spectrum after reconstruction with 2, 4,..., 256 Fourier coefficients.

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