Discrete HMMs for classification of mixtures of signals

The concept of mixtures of discrete HMMs (MDHMM) is introduced. The application of MDHMMs to the classification of mixtures of signals is described. The optimal decision rule is presented. Alternative algorithms with reduced computational load are proposed: a simplified decision statistic is defined and sub-optimal search methods are discussed. The performance of the various algorithms are analyzed on Monte-Carlo simulations.