NDLI: Study of Uncertainties in the Inversion Algorithms for Transverse Relaxation Distribution

Content Provider	IEEE Xplore Digital Library
Author	Chen Shan-shan Li Ran Yu Jie Wang Hong-zhi Zhang Xue-long
Copyright Year	2010
Abstract	Nuclear magnetic resonance (NMR) relaxation spectrum is often used as fingerprints of molecular species, structure and dynamics in the study of complex multiphase system. Inversion algorithms such as singular value decomposition (SVD), Non-negative least square (NNLS), Solid iteration rebuild technique (SIRT) have been widely used in analyzing NMR data to obtain a T1 or T2 spectrum. However, due to the ill-conditioned nature of such inversion, it is difficult to determine the reliability of the inversion result. The concrete model is realized in MATLAB according the thought of the above three algorithms in this article. We converged to the true distribution by matching up the inversion spectrum from a series of true decay data collected from the NMR analyst instrument and a noisy simulated model, then evaluated the effects of noise in the original NMR data.
Starting Page	1
Ending Page	4
File Size	1305815
Page Count	4
File Format	PDF
ISBN	9781424447121
ISSN	21517622
DOI	10.1109/ICBBE.2010.5514753
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-06-18
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Uncertainty Data analysis Fingerprint recognition Solids Nuclear magnetic resonance Magnetic analysis Mathematical model Least squares methods Singular value decomposition
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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