Principles of artificial neural networks
By: Graupe, Daniel
Material type:
BookSeries: Advanced series on circuits and systems ; volume 7.Publisher: New Jersey : World Scientific, 2013.Edition: 3rd ed.Description: xviii, 363 p. : ill. ; 26 cm.ISBN: 9789814522731Subject(s): Neural networks (Computer science)DDC classification: 006.3/2 Online resources: Location Map
Summary:
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.
| Item type | Home library | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|
| REGULAR | University of Wollongong in Dubai Main Collection | 006.32 GR PR (Browse shelf) | Available | T0013394 |
Total holds: 0
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| 006.312 WI DA Data mining : | 006.312 ZH DA Data mining applications with R / | 006.32 AD VA Advances in system optimization and control : | 006.32 GR PR Principles of artificial neural networks | 006.32 HA NE Neural networks : | 006.32 PO PR Programming PyTorch for deep learning : | 006.32 WE DE Deep learning from scratch : |
Includes bibliographical references (p. 349-356) and indexes.
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.