Creating Probabilistic Databases from Imprecise Time-Series Data
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A method is presented to construct object-related structure observables, such as size, mass, shape, and trajectories from two-dimensional plasma imaging data. The probability distributions of these observables, deduced from measurements of many realization ...
A method is presented to produce probability distributions for regional climate change in surface temperature and precipitation. The method combines a probability distribution for global mean temperature increase with the probability distributions for the ...
In this thesis a previously developed framework for modelling diversity of approximately periodic time series is considered. In this framework the diversity is modelled deterministically, exploiting the irregularity of chaos. This is an alternative to othe ...
We present a general method for maintaining estimates of the distribution of parameters in arbitrary models. This is then applied to the estimation of probability distributions over actions in value-based reinforcement learning. While this approach is simi ...
A methodology towards person clustering in meeting databases is presented in this report. Such goal is generic to a number of problem in computer vision and more specifically in content-based video indexing and retrieval. First, the audio-stream was consid ...
In this paper the approximating capabilities of fuzzy systems with overlapping Gaussian concepts are considered. The target function is assumed to be sampled either on a regular gird or according to a uniform probability density. By exploiting a connection ...
I present an introduction to some of the concepts within Bayesian networks to help a beginner become familiar with this field's theory. Bayesian networks are a combination of two different mathematical areas: graph theory and probability theory. So, I firs ...
The primary objectives of this thesis are, firstly, to develop analytical solutions for estimating the impact of contaminated sites (in particular landfills, and to a lesser extent accidentally contaminated soils) on groundwater, and secondly to evaluate m ...
We show how two-dimensional chemical shift conditional probability distributions can be extracted from experimental NMR correlation spectra of disordered solids. We show that transverse dephasing times are of central importance in determining the resolutio ...
This paper develops a framework for the mean-square analysis of adaptive filters with general data and error nonlinearities. The approach relies on energy conservation arguments and is carried out without restrictions on the probability distribution of the ...
