Probabilistic Methods In Information Theory

<p>Given a probability space, we analyze the uncertainty, that is, the amount of information of a finite system, by studying the entropy of the system. We also extend the concept of entropy to a dynamical system by introducing a measure preserving transformation on a probability space. After showing some theorems and applications of entropy theory, we study the concept of ergodicity, which helps us to further analyze the information of the system.</p>

Name thesis:degree_name

Master of Arts in Mathematics

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Mathematics

Year dc:date.available

2016

Author dc:creator

• Pachas, Erik W

Contributors dc:contributor

• Kakihara, Yuichiro

• erik pachas
• information theory
• probabilistic methods in information theory
• introduction to entropy theory
• brief introduction to ergodic theory
• entropy examples
• Other Statistics and Probability

Repository record dc:identifier

https://scholarworks.lib.csusb.edu/etd/407

OAI identifier oai:identifier

oai:scholarworks.lib.csusb.edu:etd-1464