One of the challenges a decision maker faces is choosing a suitable rough set model to use for data analysis. The traditional algebraic rough set model classifies objects into th...
Abstract—Segmenting lesions is a vital step in many computerized mass-detection schemes for digital (or digitized) mammograms. We have developed two novel lesion segmentation tec...
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
Recent probabilistic test generation approaches have proven that detecting single stuck-at faults multiple times is effective at reducing the defective part level (DPL). Unfortuna...
Yuxin Tian, Michael R. Grimaila, Weiping Shi, M. R...
We present a study into all-pole spectral envelope estimation for the case of harmonic signals. We address the problem of the selection of the model order and propose to make use ...