Utilization of characteristics of fast linear prediction based on the lattice algorithm in an analysis of time domain magnetic resonance

We examined details of the fast linear prediction (FLP) analysis of time domain data. The FLP method is introduced by Gesmar and Hansen to improve computational efficiency of the LP analysis. We focused on two characteristic features of FLP inherited from the lattice algorithm. The first is bi-directional prediction. One can obtain both forward and backward prediction models by single execution of FLP. It is found that distances between the forward and backward prediction roots in a complex plane can be used to determine a number of resonance lines. We showed that the method utilizing the distance is as effective as that using the singular value of the singular value decomposition (SVD) analysis. Secondly, the FLP method gives prediction models for all of smaller prediction orders than some given value. This character enables one to examine a prediction order dependence of spectral parameters estimated by the analysis. We found that there were significant differences in the order dependence of the estimated frequencies between true and false resonance signals.