Noise-band factor analysis of cancer Fourier transform infrared evanescent-wave fiber optical (FTIR-FEW) spectra

2002 ◽  
Author(s):  
Sydney Sukuta ◽  
Reinhard F. Bruch
Keyword(s):  
Factor Analysis ◽  
Fourier Transform ◽  
Evanescent Wave ◽  
Fourier Transform Infrared ◽  
Noise Band ◽  
Fiber Optical

How to Deal with Some Spurious Fringes in Fourier Transform Infrared Spectrometers

2008 ◽  
Vol 62 (10) ◽  
pp. 1167-1172 ◽  
Author(s):  
Jean-Joseph Max ◽  
Camille Chapados
Keyword(s):  
Factor Analysis ◽  
Spectral Analysis ◽  
Fourier Transform ◽  
Fourier Transform Infrared ◽  
Simple Method ◽  
Data Treatment ◽  
Infrared Spectrometer

Faulty fringes coming from an infrared spectrometer may creep into a spectrum. Because these come from one faulty interferogram out of many used to obtain the spectrum, these may pass unnoticed. However, they cause some problems in the data treatment of factor analysis and other spectral analysis. We present a method for detecting the faulty fringes and give a simple method to eliminate them at the interferogram accumulation level.

Factor Analysis Applied to Fourier Transform Infrared Spectra

1979 ◽  
Vol 33 (4) ◽  
pp. 351-357 ◽  
Author(s):  
Mitchell K. Antoon ◽  
Louis D'Esposito ◽  
Jack L. Koenig
Keyword(s):  
Factor Analysis ◽  
Fourier Transform ◽  
Infrared Spectra ◽  
Spectral Region ◽  
Fourier Transform Infrared ◽  
Model System ◽  
General Applicability ◽  
Polymer Systems ◽  
Number Of Components ◽  
Fourier Transform Infrared Spectra

The feasibility of applying the methods of factor analysis to Fourier transform infrared spectra is examined. The method is designed to determine the number of components contributing to a spectral region. The technique has been applied to a model system consisting of solutions of p−, o−, and m-xylenes. The method has also been used for calculating the number of independently absorbing species in several polymer systems. Spectral requirements and the general applicability of factor analysis are also discussed.

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