A new approach to time dependent AR modeling of signals and its application to analysis of the fourth heart sound
The authors present a method for estimating spectrum transition between short-length signals of succeeding frames in low-SNR cases when the transition pattern is complex and/or there are large differences in the transition patterns among the individual sets of multiframe signals. The present approach uses a linear algorithm without any basic functions. Instead, the authors use the spectrum transition constraint, and the singular value decomposition. (SVD)-based technique is applied to obtain more accurate estimates. For the analysis of multiframe signals of the fourth heart sounds obtained during a stress test, significant differences in the transition patterns are clearly detected in the spectra between patients with myocardial infarction and normal persons The significant characteristics of these transition patterns may be applied to acoustic diagnosis of heart disease. >