Application of the distributed and parallel computation in spectroscopy signal processing

The distributed and parallel computation was introduced to spectroscopy signal processing. The reflection spectra of 4 different varieties of sugar including sucrose, xylitol, maltose and dextrose were measured with FI/IR-4100 Fourier infrared spectral equipment. Each type of sugar consisted of 39 s...

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Veröffentlicht in:Guang pu xue yu guang pu fen xi Jg. 29; H. 4; S. 1074
Hauptverfasser: Chen, Yong-ming, Lin, Ping, Bao, Yi-dan, He, Yong
Format: Journal Article
Sprache:Chinesisch
Veröffentlicht: China 01.04.2009
Schlagworte:
Algorithms
Automatic Data Processing
Disaccharides - chemistry
Glucose - chemistry
Neural Networks (Computer)
Spectroscopy, Fourier Transform Infrared
Xylitol - chemistry
ISSN:1000-0593
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Abstract The distributed and parallel computation was introduced to spectroscopy signal processing. The reflection spectra of 4 different varieties of sugar including sucrose, xylitol, maltose and dextrose were measured with FI/IR-4100 Fourier infrared spectral equipment. Each type of sugar consisted of 39 samples. The distributed and parallel algorithm was executed on 2 computers with the same hardware and software systems. First, the distributed and parallel algorithm was used to read original spectral data from the text files generated by FT/IR-4100 device. Second, the data were preprocessed by distributed and parallel algorithm. The preprocessing methods include standard normalization to the maximum peak, Savizky-Golay smoothing denoising, etc. Third, search for the key discriminative wave numbers in mass spectrometry data was performed by distributed and parallel genetic algorithm (GA). At the end, the discriminative features of 24 wave numbers extracted by GA were applied as BP neural network inputs and a 3-laye
AbstractList The distributed and parallel computation was introduced to spectroscopy signal processing. The reflection spectra of 4 different varieties of sugar including sucrose, xylitol, maltose and dextrose were measured with FI/IR-4100 Fourier infrared spectral equipment. Each type of sugar consisted of 39 samples. The distributed and parallel algorithm was executed on 2 computers with the same hardware and software systems. First, the distributed and parallel algorithm was used to read original spectral data from the text files generated by FT/IR-4100 device. Second, the data were preprocessed by distributed and parallel algorithm. The preprocessing methods include standard normalization to the maximum peak, Savizky-Golay smoothing denoising, etc. Third, search for the key discriminative wave numbers in mass spectrometry data was performed by distributed and parallel genetic algorithm (GA). At the end, the discriminative features of 24 wave numbers extracted by GA were applied as BP neural network inputs and a 3-laye
Author Lin, Ping
Chen, Yong-ming
He, Yong
Bao, Yi-dan
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/19626906$$D View this record in MEDLINE/PubMed
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SubjectTerms Algorithms
Automatic Data Processing
Disaccharides - chemistry
Glucose - chemistry
Neural Networks (Computer)
Spectroscopy, Fourier Transform Infrared
Xylitol - chemistry
Title Application of the distributed and parallel computation in spectroscopy signal processing
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