This latest addition to the successful Network Biology series presents current methods for determining the entropy of networks, making it the first to cover the recently established Quantitative Graph Theory.
An excellent international team of editors and contributors provides an up-to-date outlook for the field, covering a broad range of graph entropy-related concepts and methods. The topics range from analyzing mathematical properties of methods right up to applying them in real-life areas.
Filling a gap in the contemporary literature this is an invaluable reference for a number of disciplines, including mathematicians, computer scientists, computational biologists, and structural chemists.

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Yes, you can access Mathematical Foundations and Applications of Graph Entropy by Matthias Dehmer,Frank Emmert-Streib,Zengqiang Chen,Xueliang Li,Yongtang Shi in PDF and/or ePUB format, as well as other popular books in Medicine & Biostatistics. We have over one million books available in our catalogue for you to explore.

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Year

Print ISBN

eBook ISBN

Edition

Topic

Medicine

Subtopic

Biostatistics

Cover
Related Title
Title Page
Copyright
Table of Contents
List of Contributors
Preface
Chapter 1: Entropy and Renormalization in Chaotic Visibility Graphs
Chapter 2: Generalized Entropies of Complex and Random Networks
Chapter 3: Information Flow and Entropy Production on Bayesian Networks
Chapter 4: Entropy, Counting, and Fractional Chromatic Number
Chapter 5: Graph Entropy: Recent Results and Perspectives
Chapter 6: Statistical Methods in Graphs: Parameter Estimation, Model Selection, and Hypothesis Test
Chapter 7: Graph Entropies in Texture Segmentation of Images
Chapter 8: Information Content Measures and Prediction of Physical Entropy of Organic Compounds
Chapter 9: Application of Graph Entropy for Knowledge Discovery and Data Mining in Bibliometric Data
Index
End User License Agreement

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Table of contents