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Compression of n th‐order data arrays by B‐splines. Part 2: Application to second‐order FT‐IR spectra
Author(s) -
Alsberg Bjørn K.,
Nodland Egil,
Kvalheim Olav M.
Publication year - 1994
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.1180080205
Subject(s) - principal component analysis , compression (physics) , representation (politics) , data compression , data reduction , algorithm , computation , computer science , mathematics , artificial intelligence , data mining , physics , politics , political science , law , thermodynamics
In order to improve the storage and CPU time in the numerical analysis of large two‐dimensional (hyphenated, second‐order) infrared spectra, a data‐preprocessing technique (compression) is presented which is based on B‐splines. B‐splines have been chosen as the compression method since they are wellsuited to model smooth curves. There are two primary goals of compression: a reduction of file size and a reduction of computation when analyzing the compressed representation. The compressed representation of the spectra is used as a substitute for the original representation. For the particular example used here, approximately 0.16 bit per data element was required for the compressed representation in contrast with 16 bits per data element in the uncompressed representation. The compressed representation was further analysed using principal component analysis and compared with a similar analysis on the original data set. The results shows that the principal compotent model of the compressed representation is directly comparable with the principal component model of the original data.