Uniform Transformation of Non-Separable Probability Distributions
Neural and Evolutionary Computing
2016-09-08 v1
Abstract
A theoretical framework is developed to describe the transformation that distributes probability density functions uniformly over space. In one dimension, the cumulative distribution can be used, but does not generalize to higher dimensions, or non-separable distributions. A potential function is shown to link probability density functions to their transformation, and to generalize the cumulative. A numerical method is developed to compute the potential, and examples are shown in two dimensions.
Cite
@article{arxiv.1609.01982,
title = {Uniform Transformation of Non-Separable Probability Distributions},
author = {Eric Kee},
journal= {arXiv preprint arXiv:1609.01982},
year = {2016}
}
Comments
10 pages