Accurate quantification of (1)H spectra: from finite impulse response filter design for solvent suppression to parameter estimation.
暂无分享,去创建一个
S Van Huffel | I Dologlou | L Vanhamme | P Van Hecke | T Sundin | S. Van Huffel | P. van Hecke | L. Vanhamme | T. Sundin | I. Dologlou
[1] M. Deriche,et al. Elimination of Water Signal by Postprocessing , 1993 .
[2] U. Klose. In vivo proton spectroscopy in presence of eddy currents , 1990, Magnetic resonance in medicine.
[3] Sabine Van Huffel,et al. Parameter Estimation with Prior Knowledge of Known Signal Poles for the Quantification of NMR Spectroscopy Data in the Time Domain , 1996 .
[4] Alan V. Oppenheim,et al. Discrete-Time Signal Pro-cessing , 1989 .
[5] O. Herrmann,et al. Design of nonrecursive digital filters with minimum phase , 1970 .
[6] P. Luyten,et al. Accurate quantification of in vivo 31P NMR signals using the variable projection method and prior knowledge , 1988, Magnetic resonance in medicine.
[7] D. van Ormondt,et al. SVD-based quantification of magnetic resonance signals , 1992 .
[8] D. van Ormondt,et al. Improved algorithm for noniterative time-domain model fitting to exponentially damped magnetic resonance signals , 1987 .
[9] R. Kumaresan,et al. Estimating the parameters of exponentially damped sinusoids and pole-zero modeling in noise , 1982 .
[10] K. Arun,et al. State-space and singular-value decomposition-based approximation methods for the harmonic retrieval problem , 1983 .
[11] Sabine Van Huffel,et al. Subspace-based parameter estimation of exponentially damped sinusoids using prior knowledge of frequency and phase , 1997, Signal Process..
[12] J. Schoukens,et al. Frequency domain system identification using arbitrary signals , 1997, IEEE Trans. Autom. Control..
[13] de Beer R,et al. LeuvenDepartement Elektrotechniek ESAT-SISTA / TR 1997-89 Fast removal of residual water in proton spectra 1 , 2022 .
[14] Gareth A. Morris,et al. Compensation of instrumental imperfections by deconvolution using an internal reference signal , 1988 .
[15] Ad Bax,et al. Improved solvent suppression in one-and two-dimensional NMR spectra by convolution of time-domain data , 1989 .
[16] Vanhamme,et al. Improved method for accurate and efficient quantification of MRS data with use of prior knowledge , 1997, Journal of magnetic resonance.
[17] G Zhu,et al. Post-acquisition solvent suppression by singular-value decomposition. , 1997, Journal of magnetic resonance.
[18] Petre Stoica,et al. Decentralized Control , 2018, The Control Systems Handbook.
[19] D. van Ormondt,et al. Retrieval of frequencies, amplitudes, damping factors, and phases from time-domain signals using a linear least-squares procedure , 1985 .
[20] Yung-Ya Lin,et al. A Novel Detection–Estimation Scheme for Noisy NMR Signals: Applications to Delayed Acquisition Data , 1997 .
[21] C. Sidney Burrus,et al. Constrained least square design of FIR filters without specified transition bands , 1996, IEEE Trans. Signal Process..
[22] J.H.J. Leclerc. Distortion-free suppression of the residual water peak in proton spectra by postprocessing , 1994 .
[23] Keith J. Cross. Improved Digital Filtering Technique for Solvent Suppression , 1993 .
[24] C. J. Craven,et al. The Action of Time-Domain Convolution Filters for Solvent Suppression , 1995 .