A new time-domain frequency-selective quantification algorithm

In this paper a new time-domain frequency-selective quantification algorithm is presented. Frequency-selective quantification refers to a method that analyzes spectral components in a selected frequency region, ignoring all the other components outside. The algorithm, referred to as MeFreS (Metropolis Frequency-Selective), is based on rank minimization of an opportune Hankel matrix. The minimization procedure is satisfied by the down-hill simplex method, implemented with the simulated annealing method. MeFreS does not use any preprocessing step or filter to suppress nuisance peaks, but the signal model function is directly fitted. In this manner, neither inherent signal distortions nor estimation biases to be corrected occur. The algorithm was tested with Monte Carlo simulations. A comparison with VARPRO and AMARESw algorithms was carried out. Finally, two samples of known content from NMR data were quantified.

In this paper a new time-domain frequency-selective quantification algorithm is presented. Frequency-selective quantification refers to a method that analyzes spectral components in a selected frequency region, ignoring all the other components outside. The algorithm, referred to as MeFreS (Metropolis Frequency-Selective), is based on rank minimization of an opportune Hankel matrix. The minimization procedure is satisfied by the down-hill simplex method, implemented with the simulated annealing method. MeFreS does not use any preprocessing step or filter to suppress nuisance peaks, but the signal model function is directly fitted. In this manner, neither inherent signal distortions nor estimation biases to be corrected occur. The algorithm was tested with Monte Carlo simulations. A comparison with VARPRO and AMARESw algorithms was carried out. Finally, two samples of known content from NMR data were quantified. © 2002 Elsevier Science (USA).