Gaussian apodization factor analysis for Rank analyzing of Ion mobility spectra

Evaluation of raw data on ion mobility spectrometry is very important in detection of the trace chemical of interest. It is truly ideal to reach a new technical methods that can extract ions mobility signals from all acquired raw data without manipulation of it. In many cases, weak signals are manipulated during the data collection process and some weak signals are eliminated. Quickly and clearly finding of a rank map is the main problem in resolving the elution profiles of all the chemical components in such data. In the past decade, a variety of non-iterative methods for the correct determination of the number and range of each factor based on singular value decomposition (SVD) have had widespread applications in analytical chemistry and other fields. Gaussian apodization factor analysis (GAFA) has been developed as an enhanced algorithm to assess the peak purity of the two-dimensional data, by weighting the fixed-size moving window via Gaussian formula. In GAFA method, submatrices are extracted by Gaussian apodization moving window. Therefore, each submatrix mainly characterizes the spectrum and by performing factor analysis on this Gaussian weighted submatrix, the number of principal components for each evaluated spectrum, is determined [1]. This precise and quick determination of a rank map is successfully used for extract pure components from Ion mobility spectra.