medical image registration methods which use mutual information as similarity measure have been improved in recent decades. mutual information is a basic concept of information theory which indicates the dependency of two random variables (or two images). in order to evaluate the mutual information of two images their joint probability distribution is required. several interpolation methods, su...

A new gradient technique is introduced for linear independent component analysis (ICA) based on the Edgeworth expansion of mutual information, for which the algorithm operates sequentially using fixed-point iterations. In order to address the adverse effect of outliers, a robust version of the Edgeworth expansion is adopted, in terms of robust cumulants, and robust derivatives of the Hermite po...

Established phonological theories postulate uniform syllable constituent structures. From a traditional hierarchical point of view, syllables are right branching implying a close connection between the nucleus and the coda. Articulatory Phonology in contrast suggests a stronger cohesion between onsets and nuclei than between nuclei and codas. This claim is empirically supported by the c-center ...

Among all measures of independence between random variables, mutual information is the only one that is based on information theory. Mutual information takes into account of all kinds of dependencies between variables, i.e., both the linear and non-linear dependencies. In this paper we have classified some well-known bivariate distributions into two classes of distributions based on their mutua...

A FIELD-WISE WIND RETRIEVAL ALGORITHM FOR THE NASA SCATTEROMETER Charles G. Brown Electrical and Computer Engineering Master of Science An alternative to traditional wind retrieval techniques that does not rely on numerical weather prediction winds is developed and applied in this thesis. Traditional satellite scatterometer wind retrieval algorithms consist of point-wise wind estimation and amb...

Deep learning with 3D data such as reconstructed point clouds and CAD models has received great research interests recently. However, the capability of using point clouds with convolutional neural network has been so far not fully explored. In this paper, we present a convolutional neural network for semantic segmentation and object recognition with 3D point clouds. At the core of our network i...

PURPOSE Partial volume effects (PVEs) are consequences of the limited spatial resolution in emission tomography leading to underestimation of uptake in tissues of size similar to the point spread function (PSF) of the scanner as well as activity spillover between adjacent structures. Among PVE correction methodologies, a voxel-wise mutual multiresolution analysis (MMA) was recently introduced. ...

In this paper we present a method for finding general dependencies between individual agents in a multi-agent system. We use mutual information as the general measure for dependence and demonstrate how it can be used to estimate pair-wise coupling in a 2 dimensional swarm. We then show that our technique of measuring local coupling can find phase transitions in the global behaviour of the system.