1985
DOI: 10.1016/0022-2364(85)90187-8
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Retrieval of frequencies, amplitudes, damping factors, and phases from time-domain signals using a linear least-squares procedure

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Cited by 301 publications
(147 citation statements)
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“…In the t 1 dimension of 1 H-15 N HSQC spectra, a 45 phase-shifted sine bell was applied prior to Fourier transformation, and a Lorentzian-toGaussian ®lter with NMRPipe parameters G1 10 Hz (inverse exponential width), G2 20 Hz (Gaussian width) and G3 0 (corresponding to a maximum at the ®rst point in the FID) was applied in the t 2 dimension. For the HNCACB, CBCA(CO)NH, HBHA(CBCACO)NH and (HB)CBCACO(CA)HA data sets, linear prediction (Barkhuijsen et al, 1985) was used to double the number of planes in the t 2 dimension. Where necessary, the residual water signal was reduced using a time-domain deconvolution approach (Marion et al, 1989).…”
Section: Nmr Data Processing and Analysismentioning
confidence: 99%
“…In the t 1 dimension of 1 H-15 N HSQC spectra, a 45 phase-shifted sine bell was applied prior to Fourier transformation, and a Lorentzian-toGaussian ®lter with NMRPipe parameters G1 10 Hz (inverse exponential width), G2 20 Hz (Gaussian width) and G3 0 (corresponding to a maximum at the ®rst point in the FID) was applied in the t 2 dimension. For the HNCACB, CBCA(CO)NH, HBHA(CBCACO)NH and (HB)CBCACO(CA)HA data sets, linear prediction (Barkhuijsen et al, 1985) was used to double the number of planes in the t 2 dimension. Where necessary, the residual water signal was reduced using a time-domain deconvolution approach (Marion et al, 1989).…”
Section: Nmr Data Processing and Analysismentioning
confidence: 99%
“…Residual water in the I3C-resolved NOESY spectrum was further suppressed by means of a Karhunen-Loewe transformation as implemented in NMR3D (Mitschang et al, 1991). Prior to zero-filling and window multiplication, indirect dimensions were expanded by linear prediction (Barkhuisen et al, 1985). Usually, no more than half the number of acquired real points were added in this way.…”
Section: Nmr Experimentsmentioning
confidence: 99%
“…For 1-D signals, we can cite the Kumaresan and Tufts method [13], state-space methods [14] and matrix pencil [15]. These methods and their variants have been applied successfully to NMR data, often using other acronyms such as LPSVD (Linear Prediction-Singular Value Decomposition), HSVD (Hankel-Singular Value Decomposition) and so on [16][17][18][19][20] (see also the review paper by Poullet et al [21] and the references therein for more details [26], MultiDimensional Embedding (MDE) [27] and 2-D ESPRIT [28].…”
Section: O S S I E Rmentioning
confidence: 99%