Physical models of neural networks
This lecture note volume is mainly about the recent development that connected neural network modeling to the theoretical physics of disordered systems. It gives a detailed account of the (Little-) Hopfield model and its ramifications concerning non-orthogonal and hierarchical patterns, short-term m...
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Singapore
World Scientific Pub. Co.
c1990
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| Online-Zugang: | DE-92 URL des Erstveroeffentlichers |
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| 100 | 1 | |a Geszti, Tamás |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Physical models of neural networks |c Tamás Geszti |
| 264 | 1 | |a Singapore |b World Scientific Pub. Co. |c c1990 | |
| 300 | |a viii, 143 p. |b ill | ||
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| 520 | |a This lecture note volume is mainly about the recent development that connected neural network modeling to the theoretical physics of disordered systems. It gives a detailed account of the (Little-) Hopfield model and its ramifications concerning non-orthogonal and hierarchical patterns, short-term memory, time sequences, and dynamical learning algorithms. It also offers a brief introduction to computation in layered feed-forward networks, trained by back-propagation and other methods. Kohonen's self-organizing feature map algorithm is discussed in detail as a physical ordering process. The book offers a minimum complexity guide through the often cumbersome theories developed around the Hopfield model. The physical model for the Kohonen self-organizing feature map algorithm is new, enabling the reader to better understand how and why this fascinating and somewhat mysterious tool works | ||
| 650 | 4 | |a Neural circuitry / Models | |
| 650 | 4 | |a Neural networks (Computer science) | |
| 650 | 4 | |a Neural computers | |
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Datensatz im Suchindex
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| author | Geszti, Tamás |
| author_facet | Geszti, Tamás |
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| dewey-full | 612.82011 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 612 - Human physiology |
| dewey-raw | 612.82011 |
| dewey-search | 612.82011 |
| dewey-sort | 3612.82011 |
| dewey-tens | 610 - Medicine and health |
| discipline | Informatik Medizin |
| format | Electronic eBook |
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| id | DE-604.BV044639139 |
| illustrated | Illustrated |
| indexdate | 2024-12-24T06:14:04Z |
| institution | BVB |
| isbn | 9789814434492 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030037111 |
| oclc_num | 1005226799 |
| open_access_boolean | |
| owner | DE-92 |
| owner_facet | DE-92 |
| physical | viii, 143 p. ill |
| psigel | ZDB-124-WOP ZDB-124-WOP FHN_PDA_WOP |
| publishDate | 1990 |
| publishDateSearch | 1990 |
| publishDateSort | 1990 |
| publisher | World Scientific Pub. Co. |
| record_format | marc |
| spelling | Geszti, Tamás Verfasser aut Physical models of neural networks Tamás Geszti Singapore World Scientific Pub. Co. c1990 viii, 143 p. ill txt rdacontent c rdamedia cr rdacarrier This lecture note volume is mainly about the recent development that connected neural network modeling to the theoretical physics of disordered systems. It gives a detailed account of the (Little-) Hopfield model and its ramifications concerning non-orthogonal and hierarchical patterns, short-term memory, time sequences, and dynamical learning algorithms. It also offers a brief introduction to computation in layered feed-forward networks, trained by back-propagation and other methods. Kohonen's self-organizing feature map algorithm is discussed in detail as a physical ordering process. The book offers a minimum complexity guide through the often cumbersome theories developed around the Hopfield model. The physical model for the Kohonen self-organizing feature map algorithm is new, enabling the reader to better understand how and why this fascinating and somewhat mysterious tool works Neural circuitry / Models Neural networks (Computer science) Neural computers Neuronales Netz (DE-588)4226127-2 gnd rswk-swf Modell (DE-588)4039798-1 gnd rswk-swf Nervennetz (DE-588)4041638-0 gnd rswk-swf Nervennetz (DE-588)4041638-0 s Modell (DE-588)4039798-1 s 1\p DE-604 Neuronales Netz (DE-588)4226127-2 s 2\p DE-604 Erscheint auch als Druck-Ausgabe 9789810200121 Erscheint auch als Druck-Ausgabe 9810200129 http://www.worldscientific.com/worldscibooks/10.1142/0925#t=toc Verlag URL des Erstveroeffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Geszti, Tamás Physical models of neural networks Neural circuitry / Models Neural networks (Computer science) Neural computers Neuronales Netz (DE-588)4226127-2 gnd Modell (DE-588)4039798-1 gnd Nervennetz (DE-588)4041638-0 gnd |
| subject_GND | (DE-588)4226127-2 (DE-588)4039798-1 (DE-588)4041638-0 |
| title | Physical models of neural networks |
| title_auth | Physical models of neural networks |
| title_exact_search | Physical models of neural networks |
| title_full | Physical models of neural networks Tamás Geszti |
| title_fullStr | Physical models of neural networks Tamás Geszti |
| title_full_unstemmed | Physical models of neural networks Tamás Geszti |
| title_short | Physical models of neural networks |
| title_sort | physical models of neural networks |
| topic | Neural circuitry / Models Neural networks (Computer science) Neural computers Neuronales Netz (DE-588)4226127-2 gnd Modell (DE-588)4039798-1 gnd Nervennetz (DE-588)4041638-0 gnd |
| topic_facet | Neural circuitry / Models Neural networks (Computer science) Neural computers Neuronales Netz Modell Nervennetz |
| url | http://www.worldscientific.com/worldscibooks/10.1142/0925#t=toc |
| work_keys_str_mv | AT gesztitamas physicalmodelsofneuralnetworks |