Segmentation with predictive error and recursive likelihood ratio deviation methods in material characterization

In this paper, abrupt changes detection techniques are used for segmentation of ultrasound signals in order to characterize materials. We describe the main motivations for the investigation of change detection problems. We show that the use of the Recursive Likelihood Ratio Deviation (RLRD) algorithm provides better results than the Linear Prediction Error (LPE) algorithm. The choice of the ultrasound signal length problem is used in the spectral ratio technique for determining the quality factor of a material.