Information Theory and Selected Applications

Focusing on the Shannon Measure of Information (SMI), this book delves into the concept of frustration within information theory, exploring how it can be quantified. It interprets the entropy of interacting particle systems through SMI and mutual information, examining classical examples of mixing processes. The author discusses binding systems and cooperativity phenomena, providing insights into measuring frustration. Additionally, the text outlines a method for using maximum SMI to determine optimal probability distributions, making it a significant resource for scientists in the field of information theory.