EVALUATION OF A FOURIER-TRANSFORM-BASED PATTERN-RECOGNITION ALGORITHM FOR TWO-DIMENSIONAL FLUORESCENCE DATA.
A pattern-recognition algorithm for two-dimensional fluorescence data previously reported is critically evaluated. The three spectral matching criteria - sum of the absolute value of the imaginary coefficients of the frequency-domain correlation function, sum of the absolute value of the real-negative coefficients of the frequency-domain correlation function, and the intervector distance between the abbreviated Fourier transforms of two spectra - are calculated. Spectra simulated with a computer as well as data acquired with a video fluorometer are examined. Results indicate that all three parameters are sensitive to changes in peak position, peak width, relative peak height, and intensity of background noises. This work is relevant to identification of bacteria and algae.
Publication Source (Journal or Book title)
Pau, C., & Warner, I. (1987). EVALUATION OF A FOURIER-TRANSFORM-BASED PATTERN-RECOGNITION ALGORITHM FOR TWO-DIMENSIONAL FLUORESCENCE DATA.. Applied Spectroscopy, 41 (3), 496-502. https://doi.org/10.1366/0003702874448904