Modeling brain function: the world of attractor neural networks
One of the most exciting and potentially rewarding areas of scientific research is the study of the principles and mechanisms underlying brain function. It is also of great promise to future generations of computers. A growing group of researchers, adapting knowledge and techniques from a wide range...
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge University Press
1989
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| Schlagworte: | |
| Online-Zugang: | BSB01 FHN01 Volltext |
| Zusammenfassung: | One of the most exciting and potentially rewarding areas of scientific research is the study of the principles and mechanisms underlying brain function. It is also of great promise to future generations of computers. A growing group of researchers, adapting knowledge and techniques from a wide range of scientific disciplines, have made substantial progress understanding memory, the learning process, and self organization by studying the properties of models of neural networks - idealized systems containing very large numbers of connected neurons, whose interactions give rise to the special qualities of the brain. This book introduces and explains the techniques brought from physics to the study of neural networks and the insights they have stimulated. It is written at a level accessible to the wide range of researchers working on these problems - statistical physicists, biologists, computer scientists, computer technologists and cognitive psychologists. The author presents a coherent and clear nonmechanical presentation of all the basic ideas and results. More technical aspects are restricted, wherever possible, to special sections and appendices in each chapter. The book is suitable as a text for graduate courses in physics, electrical engineering, computer science and biology |
| Beschreibung: | Title from publisher's bibliographic system (viewed on 05 Oct 2015) |
| Beschreibung: | 1 online resource (xvii, 504 pages) |
| ISBN: | 9780511623257 |
| DOI: | 10.1017/CBO9780511623257 |
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Datensatz im Suchindex
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| author | Amit, D. J. 1938- |
| author_facet | Amit, D. J. 1938- |
| author_role | aut |
| author_sort | Amit, D. J. 1938- |
| author_variant | d j a dj dja |
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| bvnumber | BV043944198 |
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| dewey-full | 591.1/88 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 591 - Specific topics in natural history of animals |
| dewey-raw | 591.1/88 |
| dewey-search | 591.1/88 |
| dewey-sort | 3591.1 288 |
| dewey-tens | 590 - Animals |
| discipline | Biologie Informatik Psychologie |
| doi_str_mv | 10.1017/CBO9780511623257 |
| format | Electronic eBook |
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| id | DE-604.BV043944198 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:39:21Z |
| institution | BVB |
| isbn | 9780511623257 |
| language | English |
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| physical | 1 online resource (xvii, 504 pages) |
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| publisher | Cambridge University Press |
| record_format | marc |
| spelling | Amit, D. J. 1938- Verfasser aut Modeling brain function the world of attractor neural networks Daniel J. Amit Cambridge Cambridge University Press 1989 1 online resource (xvii, 504 pages) txt rdacontent c rdamedia cr rdacarrier Title from publisher's bibliographic system (viewed on 05 Oct 2015) One of the most exciting and potentially rewarding areas of scientific research is the study of the principles and mechanisms underlying brain function. It is also of great promise to future generations of computers. A growing group of researchers, adapting knowledge and techniques from a wide range of scientific disciplines, have made substantial progress understanding memory, the learning process, and self organization by studying the properties of models of neural networks - idealized systems containing very large numbers of connected neurons, whose interactions give rise to the special qualities of the brain. This book introduces and explains the techniques brought from physics to the study of neural networks and the insights they have stimulated. It is written at a level accessible to the wide range of researchers working on these problems - statistical physicists, biologists, computer scientists, computer technologists and cognitive psychologists. The author presents a coherent and clear nonmechanical presentation of all the basic ideas and results. More technical aspects are restricted, wherever possible, to special sections and appendices in each chapter. The book is suitable as a text for graduate courses in physics, electrical engineering, computer science and biology Brain / Computer simulation Neural networks (Neurobiology) Neural computers Attraktor (DE-588)4140563-8 gnd rswk-swf Hirnfunktion (DE-588)4159930-5 gnd rswk-swf Gehirn (DE-588)4019752-9 gnd rswk-swf Computersimulation (DE-588)4148259-1 gnd rswk-swf Modell (DE-588)4039798-1 gnd rswk-swf Nervennetz (DE-588)4041638-0 gnd rswk-swf Neuronales Netz (DE-588)4226127-2 gnd rswk-swf Gehirn (DE-588)4019752-9 s Nervennetz (DE-588)4041638-0 s Modell (DE-588)4039798-1 s 1\p DE-604 Attraktor (DE-588)4140563-8 s 2\p DE-604 Hirnfunktion (DE-588)4159930-5 s Computersimulation (DE-588)4148259-1 s 3\p DE-604 4\p DE-604 5\p DE-604 Neuronales Netz (DE-588)4226127-2 s 6\p DE-604 Erscheint auch als Druckausgabe 978-0-521-36100-2 Erscheint auch als Druckausgabe 978-0-521-42124-9 https://doi.org/10.1017/CBO9780511623257 Verlag URL des Erstveröffentlichers 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 3\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 4\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 5\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 6\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Amit, D. J. 1938- Modeling brain function the world of attractor neural networks Brain / Computer simulation Neural networks (Neurobiology) Neural computers Attraktor (DE-588)4140563-8 gnd Hirnfunktion (DE-588)4159930-5 gnd Gehirn (DE-588)4019752-9 gnd Computersimulation (DE-588)4148259-1 gnd Modell (DE-588)4039798-1 gnd Nervennetz (DE-588)4041638-0 gnd Neuronales Netz (DE-588)4226127-2 gnd |
| subject_GND | (DE-588)4140563-8 (DE-588)4159930-5 (DE-588)4019752-9 (DE-588)4148259-1 (DE-588)4039798-1 (DE-588)4041638-0 (DE-588)4226127-2 |
| title | Modeling brain function the world of attractor neural networks |
| title_auth | Modeling brain function the world of attractor neural networks |
| title_exact_search | Modeling brain function the world of attractor neural networks |
| title_full | Modeling brain function the world of attractor neural networks Daniel J. Amit |
| title_fullStr | Modeling brain function the world of attractor neural networks Daniel J. Amit |
| title_full_unstemmed | Modeling brain function the world of attractor neural networks Daniel J. Amit |
| title_short | Modeling brain function |
| title_sort | modeling brain function the world of attractor neural networks |
| title_sub | the world of attractor neural networks |
| topic | Brain / Computer simulation Neural networks (Neurobiology) Neural computers Attraktor (DE-588)4140563-8 gnd Hirnfunktion (DE-588)4159930-5 gnd Gehirn (DE-588)4019752-9 gnd Computersimulation (DE-588)4148259-1 gnd Modell (DE-588)4039798-1 gnd Nervennetz (DE-588)4041638-0 gnd Neuronales Netz (DE-588)4226127-2 gnd |
| topic_facet | Brain / Computer simulation Neural networks (Neurobiology) Neural computers Attraktor Hirnfunktion Gehirn Computersimulation Modell Nervennetz Neuronales Netz |
| url | https://doi.org/10.1017/CBO9780511623257 |
| work_keys_str_mv | AT amitdj modelingbrainfunctiontheworldofattractorneuralnetworks |