— Many decision systems rely on a precisely known Markov Chain model to guarantee optimal performance, and this paper considers the online estimation of unknown, nonstationary Ma...
Abstract. A nonparametric Bayesian extension of Independent Components Analysis (ICA) is proposed where observed data Y is modelled as a linear superposition, G, of a potentially i...
— We investigate modeling and recognition of object manipulation actions for the purpose of imitation based learning in robotics. To model the process, we are using a combination...
Background: Remote homology detection is a challenging problem in Bioinformatics. Arguably, profile Hidden Markov Models (pHMMs) are one of the most successful approaches in addre...
Abstract. This paper proposes an entropy based Markov chain (EMC) fusion technique and demonstrates its applications in multisensor fusion. Self-entropy and conditional entropy, wh...