Application of linear prediction singular value decomposition for processingin vivo NMR data with low signal-to-noise ratio

Jorge L. Galazzo; James E. Bailey

doi:10.1007/bf01876214

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Application of linear prediction singular value decomposition for processingin vivo NMR data with low signal-to-noise ratio

Jorge L. Galazzo James E. Bailey

Year: 1989 Journal: Biotechnology Techniques Vol: 3 (1)Pages: 13-18 Publisher: Springer Science+Business Media

DOI: 10.1007/bf01876214

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Keywords:

Singular value decomposition Nuclear magnetic resonance spectroscopy Nuclear magnetic resonance Intracellular Fourier transform Analytical Chemistry (journal) SIGNAL (programming language) Biological system Chemistry Noise (video) Transformation (genetics) Sensitivity (control systems) Chromatography Physics Mathematics Computer science Biology Algorithm Mathematical analysis Biochemistry

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NMR spectroscopy and applications

Physical Sciences → Physics and Astronomy → Nuclear and High Energy Physics

Advanced MRI Techniques and Applications

Health Sciences → Medicine → Radiology, Nuclear Medicine and Imaging

Spectroscopy and Chemometric Analyses

Physical Sciences → Chemistry → Analytical Chemistry

Application of linear prediction singular value decomposition for processingin vivo NMR data with low signal-to-noise ratio

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