پديدآورندگان :
Alinoori Amir Hossein Spectroscopy and microelectronic department, Institute of Materials and Energy, Iranian Space Research Center, Isfahan, Po.Box: 81395-619, Iran , Hajialigol Saeed Spectroscopy and microelectronic department, Institute of Materials and Energy, Iranian Space Research Center, Isfahan, Po.Box: 81395-619, Iran , Ghorashi Seyed Alireza Spectroscopy and microelectronic department, Institute of Materials and Energy, Iranian Space Research Center, Isfahan, Po.Box: 81395-619, Iran , Zamani Joharestani Mahdi Spectroscopy and microelectronic department, Institute of Materials and Energy, Iranian Space Research Center, Isfahan, Po.Box: 81395-619, Iran
كليدواژه :
ion mobility spectrometry , Gaussian apodization factor analysis discrete Gabor transforms , signal denoising , Signal , to , Noise Ratio , spike removal algoritm
چكيده فارسي :
Overlapping dual mode handheld Ion mobility spectrometry peaks may occur and can really complicate the interpretation and analysis of data. Obtaining appropriate data analysis tools, which focus on the data to detect overlapped/embedded regions and to find the number of pure components that are hidden in these regions, is a problem in common analytical applications [1]. An algorithm based on Gaussian apodization factor analysis (GAFA) was applied to resolve different types of overlapped simulated and real complex data of dual mode handheld Ion mobility spectrometry. New algorithm for analysing the structure of raw data based on discrete Gabor transforms combined with Gaussian apodization factor analysis (DGT-GAFA) was applied to find signal and noise components in frequency domain by applying Gaussian apodization factor analysis and remove unwanted components in frequency domain that lead to increase in signal to noise ratio (SNR) and preserve of weak signals. The DGT-GAFA method was applied to amplify significant information, detection of target signals [2]. This Peak Resolution algorithm finds spectra of pure component with GAFA one by one and eliminates obtained components from a data matrix and search for next pure component spectra until all the components are determined.
