Initially, the spectra were truncated to 750 2000 cm−1 and converted to second derivative spectra, which have been shown to be optimal for many FTIR spectral analysis models (Paschalis et al, 1996; Gao et al, 1999; Beleites et al, 2005; Das et al, 2007).
During the last two decades or so, NIR spectroscopy has made marked progress in many aspects from instrumentation, spectral analysis, and applications and has been used extensively as a powerful technique in a variety of basic as well as applied sciences.
Therefore, many authors have investigated the spectral analysis of differential and discrete operators [1 10].
Spectral analysis suggests that many grains are much less than 50 micrometers wide; that's light enough for the charges to briefly levitate the grains in the weak gravity of Eros.
Although spectral analysis has been used by many reflectometry devices [ 16], it may not provide the required accuracy for biological interpretation of a DTP standard.
ANN, as a multivariate calibration method, is very useful in spectral analysis because the simultaneous inclusion of many spectral wavelengths instead of using a single wavelength greatly improves the precision and predictive ability of the method [21].
Ultrasonic spectral analysis techniques have been used by many investigators to add information regarding tissue microstructure to images generated by conventional ultrasound [ 25].
Hence, many period analysis methods including fast Fourier transform (FFT), maximum entropy spectral analysis (MESA) and wavelet analysis (WA) have been developed to study this issue.
In practice, many different approaches to time series analysis are used, including Fourier spectral analysis, Bayesian modeling, neural networks, and various pattern search methods.
By performing spectral analysis using wavelet transform, EEG signals consisting of many data points can be compressed into few features [ 20– 23].
