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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01zg64tp23b
Title: COMPUTATION OF INFORMATION MEASURES
Authors: Zhan, Shuxin
Advisors: Verdu, Sergio
Contributors: Lieb, Elliott
Department: Mathematics
Class Year: 2015
Abstract: For well-behaved distributions, mutual information can computed using a simple identity with the two distribution’s marginal and conditional entropies. However, when these entropies are ill-defined, more powerful methods are required. This thesis aims to calculate the mutual information of one such distribution given by p(x) = 1/xlog2(x). This is the first known attempt to approximate mutual information of distributions such as these. While I was able to numerically approximate the mutual information of this distribution as well as find meaningful lower bounds, proving the existence of an upper bound remains an open problem.
Extent: 26 pages
URI: http://arks.princeton.edu/ark:/88435/dsp01zg64tp23b
Type of Material: Princeton University Senior Theses
Language: en_US
Appears in Collections:Mathematics, 1934-2016

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