Information Theory and Selected Applications

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The book delves into the Shannon Measure of Information (SMI) and its applications in quantifying frustration within information theory. It explores the entropy of interacting particle systems through SMI and mutual information, examining how these concepts relate to processes like mixing and assimilation. Additionally, it discusses binding systems and cooperativity phenomena, offering a method for utilizing maximum SMI to derive optimal probability distributions. This work is a significant resource for scientists interested in the intersections of information theory and its practical applications.