In this paper we present an improvement of the 2DUPEN algorithm (I2DUPEN) obtained by applying data windowing and Singular Value Decomposition (SVD) filtering. The presented I2DUPEN method solves a regularized weighted least squares problem where the weights are related to the statistics of the data. The SVD filtering is applied to reduce the problem size. The preliminary results on real 2D Nuclear Magnetic Resonance data show the potentiality of this strategy to improve the performance of the algorithm preserving reconstructions of good quality. Just as the original 2DUPEN algorithm, I2DUPEN can be used on a wide range of NMR data obtained from different kinds of samples, from multi-scale length porous materials to biological samples.
Bortolotti, V., Brown, R., Fantazzini, P., Landi, G., Zama, F. (2018). I2DUPEN: Improved 2DUPEN algorithm for inversion of two-dimensional NMR data. MICROPOROUS AND MESOPOROUS MATERIALS, 269, 195-198 [10.1016/j.micromeso.2017.04.038].
I2DUPEN: Improved 2DUPEN algorithm for inversion of two-dimensional NMR data
Bortolotti, V.;Brown, R. J. S.;Fantazzini, P.;Landi, G.;Zama, F
2018
Abstract
In this paper we present an improvement of the 2DUPEN algorithm (I2DUPEN) obtained by applying data windowing and Singular Value Decomposition (SVD) filtering. The presented I2DUPEN method solves a regularized weighted least squares problem where the weights are related to the statistics of the data. The SVD filtering is applied to reduce the problem size. The preliminary results on real 2D Nuclear Magnetic Resonance data show the potentiality of this strategy to improve the performance of the algorithm preserving reconstructions of good quality. Just as the original 2DUPEN algorithm, I2DUPEN can be used on a wide range of NMR data obtained from different kinds of samples, from multi-scale length porous materials to biological samples.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.