Bayesian Signal Classifier

Abstract

This article points out the limitations of vectoral input pattern on density estimation and Bayesian classification. A continuous Bayesian classifier is proposed to tackle these limitations. The classifier accepts signal as input pattern; thus the problem of optimal description length selection is avoided. The algorithm is evaluated on signal clustering and distribution classification.