Bayesian networks are a powerful probabilistic representation, and their use for classification has received considerable attention. However, they tend to perform poorly when lear...
We consider state estimation of a Markov stochastic process using an ad hoc wireless sensor network (WSN) based on noisy linear observations. Due to power and bandwidth constraint...
Eric J. Msechu, Alejandro Ribeiro, Stergios I. Rou...
Grouping algorithms based on histograms over measured image features have very successfully been applied to textured image segmentation [2, 11, 6]. However, the competing goals of...
A novel methodology for circuit design and automatic layout generation is proposed for a class of mixed-signal circuits in presence of layout parasitics and substrate induced nois...
Paolo Miliozzi, Iasson Vassiliou, Edoardo Charbon,...
What happens to the optimal interpretation of noisy data when there exists more than one equally plausible interpretation of the data? In a Bayesian model-learning framework the a...