This paper presents an algorithm for inferring a Structured Hidden Markov Model (S-HMM) from a set of sequences. The S-HMMs are a sub-class of the Hierarchical Hidden Markov Model...
We apply a type of generative modelling to the problem of blind source separation in which prior knowledge about the latent source signals, such as time-varying auto-correlation a...
—In this paper, we present a new spectrum-hole prediction model for cognitive radio (CR) systems based on the IEEE 802.11 wireless local areas networks. We have also analyzed the...
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
—This paper introduces a new sensory system for the 2-D detection, tracking, and prediction of human motions. Using the data acquired through the sensory system, a model of a hum...