This paper develops a mathematical and computational framework for analyzing the expected perfor-mance of Bayesian data fusion, or joint statistical inference, within a sensor network. We use variational techniques to obtain the posterior expectation as the optimal fusion rule under a deterministic

utilize an approximate variational Bayesian framework and obtain a fully automatic fusion algorithm. Simulation results demonstrate that the proposed algorithm outperforms existing EEG/fMRI fusion methods. Index Terms — EEG, fMRI, total variation (TV), variational Bayesian methods.

The principle aim of this dissertation is to investigate the philosophical application of quantum information theory to interpretational issues regarding the theory of quantum mechanics. Recently, quantum information theory has emerged as a potential source for such an interpretation. The main

in Bayesian inductive logic, and to compare this logic with a closely related logic. 2 This version of the Calibration Norm presumes that all constraints on degrees of belief are mediated by evidence of physical probabilities. While this is an appropriate assumption in the context of our semantics

of knowledge and a book in Her lotus hands. Dedicated to the Lotus Feet of the revered Sadguru. This thesis presents a new active mask (AM) framework and an algorithm for segmenta-tion of digital images, particularly those of punctate patterns from fluorescence microscopy. Fluorescence microscopy has greatly

Abstract: This paper describes how multisensor data fusion increases reliability of pedestrian detection while using a Bayesian combination of features. The clue is to combine in a probabilistic framework, the detecting capabilities of sensors for identifying pedestrians located along the vehicle

. Section III relates relative trust to information and cultural variables. Section IV studies the effect of relative trust on trade, Section V on portfolio investments, and Section VI on foreign direct investments. Finally, Section VII concludes. I Theoretical Framework How does trust enter economic

. Moreover they are either p-torsion free or else infinitely many of them contain p-torsion. By means of techniques related to fusion systems we exhibit concrete examples where p-torsion appears and compute explicitly the cellularization.

recovery of signals when groups of dependent projections are taken at random. We find a penalty factor on the number of required measurements with respect to the standard CS scheme that employs conventional independent measurement selection and evaluate the accuracy of the predicted penalty through

with the event realized. Formally: where θ ∈ (1/2, 1). Because the prior is common and all the information is public, all players have common posterior beliefs about the likelihood of each event. Also, in this simple framework, bayesian updating implies that the posterior belief depends exclusively