Principles of artificial neural networks:
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
[Hackensack] New Jersey
World Scientific
[2013]
|
| Edition: | 3rd edition |
| Series: | Advanced series on circuits and systems
v. 7 |
| Subjects: | |
| Online Access: | UER01 |
| Item Description: | Description based on print version record |
| Physical Description: | 1 online resource (xviii, 363 pages) illustrations |
| ISBN: | 9789814522748 9789814522731 9814522732 9781299770935 |
Staff View
MARC
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| 245 | 1 | 0 | |a Principles of artificial neural networks |c Daniel Graupe |
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| 264 | 4 | |c © 2013 | |
| 300 | |a 1 online resource (xviii, 363 pages) |b illustrations | ||
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| 490 | 0 | |a Advanced series on circuits and systems |v v. 7 | |
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| 505 | 8 | |a Artificial neural networks are most suitable for solving problems that are complex, ill-defined, highly nonlinear, of many and different variables, and/or stochastic. Such problems are abundant in medicine, in finance, in security and beyond. This volume covers the basic theory and architecture of the major artificial neural networks. Uniquely, it presents 18 complete case studies of applications of neural networks in various fields, ranging from cell-shape classification to micro-trading in finance and to constellation recognition - all with their respective source codes. These case studies demonstrate to the readers in detail how such case studies are designed and executed and how their specific results are obtained. The book is written for a one-semester graduate or senior-level undergraduate course on artificial neural networks. It is also intended to be a self-study and a reference text for scientists, engineers and for researchers in medicine, finance and data mining | |
| 650 | 7 | |a COMPUTERS / General |2 bisacsh | |
| 650 | 7 | |a Neural networks (Computer science) |2 fast | |
| 650 | 4 | |a Neural networks (Computer science) | |
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Record in the Search Index
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| author | Graupe, Daniel |
| author_GND | (DE-588)1129263053 |
| author_facet | Graupe, Daniel |
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| contents | Artificial neural networks are most suitable for solving problems that are complex, ill-defined, highly nonlinear, of many and different variables, and/or stochastic. Such problems are abundant in medicine, in finance, in security and beyond. This volume covers the basic theory and architecture of the major artificial neural networks. Uniquely, it presents 18 complete case studies of applications of neural networks in various fields, ranging from cell-shape classification to micro-trading in finance and to constellation recognition - all with their respective source codes. These case studies demonstrate to the readers in detail how such case studies are designed and executed and how their specific results are obtained. The book is written for a one-semester graduate or senior-level undergraduate course on artificial neural networks. It is also intended to be a self-study and a reference text for scientists, engineers and for researchers in medicine, finance and data mining |
| ctrlnum | (ZDB-4-EBA)622050 (OCoLC)857066058 (DE-599)BVBBV043039288 |
| dewey-full | 006.32 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.32 |
| dewey-search | 006.32 |
| dewey-sort | 16.32 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| edition | 3rd edition |
| format | Electronic eBook |
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| id | DE-604.BV043039288 |
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| indexdate | 2024-07-10T07:15:42Z |
| institution | BVB |
| isbn | 9789814522748 9789814522731 9814522732 9781299770935 |
| language | English |
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| series2 | Advanced series on circuits and systems |
| spelling | Graupe, Daniel Verfasser (DE-588)1129263053 aut Principles of artificial neural networks Daniel Graupe 3rd edition [Hackensack] New Jersey World Scientific [2013] © 2013 1 online resource (xviii, 363 pages) illustrations txt rdacontent c rdamedia cr rdacarrier Advanced series on circuits and systems v. 7 Description based on print version record Artificial neural networks are most suitable for solving problems that are complex, ill-defined, highly nonlinear, of many and different variables, and/or stochastic. Such problems are abundant in medicine, in finance, in security and beyond. This volume covers the basic theory and architecture of the major artificial neural networks. Uniquely, it presents 18 complete case studies of applications of neural networks in various fields, ranging from cell-shape classification to micro-trading in finance and to constellation recognition - all with their respective source codes. These case studies demonstrate to the readers in detail how such case studies are designed and executed and how their specific results are obtained. The book is written for a one-semester graduate or senior-level undergraduate course on artificial neural networks. It is also intended to be a self-study and a reference text for scientists, engineers and for researchers in medicine, finance and data mining COMPUTERS / General bisacsh Neural networks (Computer science) fast Neural networks (Computer science) Neuronales Netz (DE-588)4226127-2 gnd rswk-swf 1\p (DE-588)4151278-9 Einführung gnd-content Neuronales Netz (DE-588)4226127-2 s 2\p DE-604 Erscheint auch als Druck-Ausgabe Graupe, Daniel Principles of artificial neural networks 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 | Graupe, Daniel Principles of artificial neural networks Artificial neural networks are most suitable for solving problems that are complex, ill-defined, highly nonlinear, of many and different variables, and/or stochastic. Such problems are abundant in medicine, in finance, in security and beyond. This volume covers the basic theory and architecture of the major artificial neural networks. Uniquely, it presents 18 complete case studies of applications of neural networks in various fields, ranging from cell-shape classification to micro-trading in finance and to constellation recognition - all with their respective source codes. These case studies demonstrate to the readers in detail how such case studies are designed and executed and how their specific results are obtained. The book is written for a one-semester graduate or senior-level undergraduate course on artificial neural networks. It is also intended to be a self-study and a reference text for scientists, engineers and for researchers in medicine, finance and data mining COMPUTERS / General bisacsh Neural networks (Computer science) fast Neural networks (Computer science) Neuronales Netz (DE-588)4226127-2 gnd |
| subject_GND | (DE-588)4226127-2 (DE-588)4151278-9 |
| title | Principles of artificial neural networks |
| title_auth | Principles of artificial neural networks |
| title_exact_search | Principles of artificial neural networks |
| title_full | Principles of artificial neural networks Daniel Graupe |
| title_fullStr | Principles of artificial neural networks Daniel Graupe |
| title_full_unstemmed | Principles of artificial neural networks Daniel Graupe |
| title_short | Principles of artificial neural networks |
| title_sort | principles of artificial neural networks |
| topic | COMPUTERS / General bisacsh Neural networks (Computer science) fast Neural networks (Computer science) Neuronales Netz (DE-588)4226127-2 gnd |
| topic_facet | COMPUTERS / General Neural networks (Computer science) Neuronales Netz Einführung |
| work_keys_str_mv | AT graupedaniel principlesofartificialneuralnetworks |