Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
Sparse multidimensional iterative lineshape-enhanced (SMILE) reconstruction of both non-uniformly sampled and conventional NMR data
by
Bax, Ad
, Torchia, Dennis A.
, Delaglio, Frank
, Ying, Jinfa
in
Algorithms
/ Biochemistry
/ Biological and Medical Physics
/ Biophysics
/ Computer applications
/ Computer Simulation
/ Data processing
/ Fourier Analysis
/ Fourier transforms
/ Linear prediction
/ NMR
/ Noise
/ Noise levels
/ Nuclear magnetic resonance
/ Nuclear Magnetic Resonance, Biomolecular - methods
/ Physics
/ Physics and Astronomy
/ Point spread functions
/ Reconstruction
/ Robustness
/ Sensitivity and Specificity
/ Signal-To-Noise Ratio
/ Software
/ Spectra
/ Spectroscopy/Spectrometry
/ Thermal noise
/ Time
/ Time domain analysis
2017
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Sparse multidimensional iterative lineshape-enhanced (SMILE) reconstruction of both non-uniformly sampled and conventional NMR data
by
Bax, Ad
, Torchia, Dennis A.
, Delaglio, Frank
, Ying, Jinfa
in
Algorithms
/ Biochemistry
/ Biological and Medical Physics
/ Biophysics
/ Computer applications
/ Computer Simulation
/ Data processing
/ Fourier Analysis
/ Fourier transforms
/ Linear prediction
/ NMR
/ Noise
/ Noise levels
/ Nuclear magnetic resonance
/ Nuclear Magnetic Resonance, Biomolecular - methods
/ Physics
/ Physics and Astronomy
/ Point spread functions
/ Reconstruction
/ Robustness
/ Sensitivity and Specificity
/ Signal-To-Noise Ratio
/ Software
/ Spectra
/ Spectroscopy/Spectrometry
/ Thermal noise
/ Time
/ Time domain analysis
2017
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Sparse multidimensional iterative lineshape-enhanced (SMILE) reconstruction of both non-uniformly sampled and conventional NMR data
by
Bax, Ad
, Torchia, Dennis A.
, Delaglio, Frank
, Ying, Jinfa
in
Algorithms
/ Biochemistry
/ Biological and Medical Physics
/ Biophysics
/ Computer applications
/ Computer Simulation
/ Data processing
/ Fourier Analysis
/ Fourier transforms
/ Linear prediction
/ NMR
/ Noise
/ Noise levels
/ Nuclear magnetic resonance
/ Nuclear Magnetic Resonance, Biomolecular - methods
/ Physics
/ Physics and Astronomy
/ Point spread functions
/ Reconstruction
/ Robustness
/ Sensitivity and Specificity
/ Signal-To-Noise Ratio
/ Software
/ Spectra
/ Spectroscopy/Spectrometry
/ Thermal noise
/ Time
/ Time domain analysis
2017
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Sparse multidimensional iterative lineshape-enhanced (SMILE) reconstruction of both non-uniformly sampled and conventional NMR data
Journal Article
Sparse multidimensional iterative lineshape-enhanced (SMILE) reconstruction of both non-uniformly sampled and conventional NMR data
2017
Request Book From Autostore
and Choose the Collection Method
Overview
Implementation of a new algorithm, SMILE, is described for reconstruction of non-uniformly sampled two-, three- and four-dimensional NMR data, which takes advantage of the known phases of the NMR spectrum and the exponential decay of underlying time domain signals. The method is very robust with respect to the chosen sampling protocol and, in its default mode, also extends the truncated time domain signals by a modest amount of non-sampled zeros. SMILE can likewise be used to extend conventional uniformly sampled data, as an effective multidimensional alternative to linear prediction. The program is provided as a plug-in to the widely used NMRPipe software suite, and can be used with default parameters for mainstream application, or with user control over the iterative process to possibly further improve reconstruction quality and to lower the demand on computational resources. For large data sets, the method is robust and demonstrated for sparsities down to ca 1%, and final all-real spectral sizes as large as 300 Gb. Comparison between fully sampled, conventionally processed spectra and randomly selected NUS subsets of this data shows that the reconstruction quality approaches the theoretical limit in terms of peak position fidelity and intensity. SMILE essentially removes the noise-like appearance associated with the point-spread function of signals that are a default of five-fold above the noise level, but impacts the actual thermal noise in the NMR spectra only minimally. Therefore, the appearance and interpretation of SMILE-reconstructed spectra is very similar to that of fully sampled spectra generated by Fourier transformation.
Publisher
Springer Netherlands,Springer Nature B.V
Subject
This website uses cookies to ensure you get the best experience on our website.