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|a Rosenberg, Eric.
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|a Fractal dimensions of networks /
|c Eric Rosenberg.
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| 264 |
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|a Cham, Switzerland :
|b Springer,
|c [2020]
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|a 1 online resource (xx, 524 pages)
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|a Introduction -- Networks : introductory material -- Fractals : introductory material -- Topological and box counting dimensions -- Hausdorff, similarity, and packing dimensions -- Computing the box counting dimension -- Network box counting dimensions -- Network box counting heuristics -- Correlation dimension -- Computing the correlation dimension -- Network correlation dimension -- Dimensions of infinite networks -- Similarity dimension of infinite networks -- Information dimension -- Network information dimension -- Generalized dimensions and multifractals -- Multifractal networks -- Generalized Hausdorf dimensions of networks -- Lacunarity -- Other dimensions -- Coarse graining and renormalization -- Other network dimensions -- Supplemental material.
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| 520 |
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|a Current interest in fractal dimensions of networks is the result of more than a century of previous research on dimensions. Fractal Dimensions of Networks ties the theory and methods for computing fractal dimensions of networks to the classical theory of dimensions of geometric objects. The goal of the book is to provide a unified treatment of fractal dimensions of sets and networks. Since almost all of the major concepts in fractal dimensions originated in the study of sets, the book achieves this goal by first clearly presenting, with an abundance of examples and illustrations, the theory and algorithms for sets, and then showing how the theory and algorithms have been applied to networks. For example, the book presents the classical theory and algorithms for the box counting dimension for sets, and then presents the box counting dimension for networks. All the major fractal dimensions are studied, e.g., the correlation dimension, the information dimension, the Hausdorff dimension, the multifractal spectrum, as well as many lesser known dimensions. Algorithm descriptions are accompanied by worked examples, with many applications of the methods presented. · Presentation of a unified view of fractal dimensions and the relationship between computing these dimensions for geometric objects and computing them for networks · A historical view of the different dimensions, starting with Euclid, presented in a form that is not overly mathematical · Many applications of the methods are discussed in a broad range of fields: art, biology, cosmology, food processing, marine science, neurology, etc. · Many examples are provided to illustrate the computational methods · Includes exercises throughout, ranging in difficulty from simple to research level. --
|c Provided by publisher.
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| 504 |
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|a Includes bibliographical references and index.
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| 588 |
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|a Description based on online resource; title from digital title page (viewed on August 13, 2020).
|
| 650 |
|
0 |
|a Computer networks
|x Mathematics.
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| 650 |
|
0 |
|a Fractals.
|0 http://id.loc.gov/authorities/subjects/sh85051147
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| 650 |
|
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|a Computer networks
|x Mathematics
|2 fast
|0 (OCoLC)fst00872327
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| 650 |
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7 |
|a Fractals
|2 fast
|0 (OCoLC)fst00933507
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| 655 |
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|a Electronic books.
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| 655 |
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4 |
|a Electronic books.
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| 776 |
0 |
8 |
|i Print version:
|z 3030431681
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|t Library of Congress classification
|a TK5105.5 .R67 2020
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|u https://link.springer.com/10.1007/978-3-030-43169-3
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|g ebooks
|i 12622191
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