Discrete mathematics of neural networks: selected topics
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Philadelphia, Pa.
Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104)
2001
|
| Schriftenreihe: | SIAM monographs on discrete mathematics and applications
8 |
| Schlagworte: | |
| Online-Zugang: | TUM01 UBW01 UBY01 UER01 Volltext |
| Beschreibung: | Mode of access: World Wide Web. - System requirements: Adobe Acrobat Reader Includes bibliographical references (p. 119-125) and index Artificial Neural Networks -- Boolean Functions -- Threshold Functions -- Number of Threshold Functions -- Sizes of Weights for Threshold Functions -- Threshold Order -- Threshold Networks and Boolean Functions -- Specifying Sets -- Neural Network Learning -- Probabilistic Learning -- VC-Dimensions of Neural Networks -- The Complexity of Learning -- Boltzmann Machines and Combinatorial Optimization This concise, readable book provides a sampling of the very large, active, and expanding field of artificial neural network theory. It considers select areas of discrete mathematics linking combinatorics and the theory of the simplest types of artificial neural networks. Neural networks have emerged as a key technology in many fields of application, and an understanding of the theories concerning what such systems can and cannot do is essential The author discusses interesting connections between special types of Boolean functions and the simplest types of neural networks. Some classical results are presented with accessible proofs, together with some more recent perspectives, such as those obtained by considering decision lists. In addition, probabilistic models of neural network learning are discussed. Graph theory, some partially ordered set theory, computational complexity, and discrete probability are among the mathematical topics involved. Pointers to further reading and an extensive bibliography make this book a good starting point for research in discrete mathematics and neural networks |
| Beschreibung: | 1 Online-Ressource (xi, 131 Seiten) |
| ISBN: | 9780898714807 089871480X |
| DOI: | 10.1137/1.9780898718539 |
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| 500 | |a This concise, readable book provides a sampling of the very large, active, and expanding field of artificial neural network theory. It considers select areas of discrete mathematics linking combinatorics and the theory of the simplest types of artificial neural networks. Neural networks have emerged as a key technology in many fields of application, and an understanding of the theories concerning what such systems can and cannot do is essential | ||
| 500 | |a The author discusses interesting connections between special types of Boolean functions and the simplest types of neural networks. Some classical results are presented with accessible proofs, together with some more recent perspectives, such as those obtained by considering decision lists. In addition, probabilistic models of neural network learning are discussed. Graph theory, some partially ordered set theory, computational complexity, and discrete probability are among the mathematical topics involved. Pointers to further reading and an extensive bibliography make this book a good starting point for research in discrete mathematics and neural networks | ||
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Datensatz im Suchindex
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| id | DE-604.BV039747174 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T00:10:18Z |
| institution | BVB |
| isbn | 9780898714807 089871480X |
| language | English |
| lccn | 00067940 |
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| physical | 1 Online-Ressource (xi, 131 Seiten) |
| psigel | ZDB-72-SIA |
| publishDate | 2001 |
| publishDateSearch | 2001 |
| publishDateSort | 2001 |
| publisher | Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104) |
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| series | SIAM monographs on discrete mathematics and applications |
| series2 | SIAM monographs on discrete mathematics and applications |
| spelling | Anthony, Martin 1967- Verfasser (DE-588)114372675 aut Discrete mathematics of neural networks selected topics Martin Anthony Philadelphia, Pa. Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104) 2001 1 Online-Ressource (xi, 131 Seiten) txt rdacontent c rdamedia cr rdacarrier SIAM monographs on discrete mathematics and applications [8] Mode of access: World Wide Web. - System requirements: Adobe Acrobat Reader Includes bibliographical references (p. 119-125) and index Artificial Neural Networks -- Boolean Functions -- Threshold Functions -- Number of Threshold Functions -- Sizes of Weights for Threshold Functions -- Threshold Order -- Threshold Networks and Boolean Functions -- Specifying Sets -- Neural Network Learning -- Probabilistic Learning -- VC-Dimensions of Neural Networks -- The Complexity of Learning -- Boltzmann Machines and Combinatorial Optimization This concise, readable book provides a sampling of the very large, active, and expanding field of artificial neural network theory. It considers select areas of discrete mathematics linking combinatorics and the theory of the simplest types of artificial neural networks. Neural networks have emerged as a key technology in many fields of application, and an understanding of the theories concerning what such systems can and cannot do is essential The author discusses interesting connections between special types of Boolean functions and the simplest types of neural networks. Some classical results are presented with accessible proofs, together with some more recent perspectives, such as those obtained by considering decision lists. In addition, probabilistic models of neural network learning are discussed. Graph theory, some partially ordered set theory, computational complexity, and discrete probability are among the mathematical topics involved. Pointers to further reading and an extensive bibliography make this book a good starting point for research in discrete mathematics and neural networks Mathematik Neural networks (Computer science) / Mathematics Neuronales Netz (DE-588)4226127-2 gnd rswk-swf Diskrete Mathematik (DE-588)4129143-8 gnd rswk-swf Neuronales Netz (DE-588)4226127-2 s Diskrete Mathematik (DE-588)4129143-8 s DE-604 Erscheint auch als Druckausgabe 089871480X Erscheint auch als Druckausgabe 9780898714807 SIAM monographs on discrete mathematics and applications 8 (DE-604)BV047230149 8 https://doi.org/10.1137/1.9780898718539 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Anthony, Martin 1967- Discrete mathematics of neural networks selected topics SIAM monographs on discrete mathematics and applications Mathematik Neural networks (Computer science) / Mathematics Neuronales Netz (DE-588)4226127-2 gnd Diskrete Mathematik (DE-588)4129143-8 gnd |
| subject_GND | (DE-588)4226127-2 (DE-588)4129143-8 |
| title | Discrete mathematics of neural networks selected topics |
| title_auth | Discrete mathematics of neural networks selected topics |
| title_exact_search | Discrete mathematics of neural networks selected topics |
| title_full | Discrete mathematics of neural networks selected topics Martin Anthony |
| title_fullStr | Discrete mathematics of neural networks selected topics Martin Anthony |
| title_full_unstemmed | Discrete mathematics of neural networks selected topics Martin Anthony |
| title_short | Discrete mathematics of neural networks |
| title_sort | discrete mathematics of neural networks selected topics |
| title_sub | selected topics |
| topic | Mathematik Neural networks (Computer science) / Mathematics Neuronales Netz (DE-588)4226127-2 gnd Diskrete Mathematik (DE-588)4129143-8 gnd |
| topic_facet | Mathematik Neural networks (Computer science) / Mathematics Neuronales Netz Diskrete Mathematik |
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