ISBN: 9780792395676
ID: 6389616
Feed-Forward Neural Networks: Vector Decomposition Analysis, Modelling and Analog Implementation presents a novel method for the mathematical analysis of neural networks that learn according to the back-propagation algorithm. The book also discusses some other recent alternative algorithms for hardware implemented perception-like neural networks. The method permits a simple analysis of the Feed-Forward Neural Networks: Vector Decomposition Analysis, Modelling and Analog Implementation presents a novel method for the mathematical analysis of neural networks that learn according to the back-propagation algorithm. The book also discusses some other recent alternative algorithms for hardware implemented perception-like neural networks. The method permits a simple analysis of the learning behaviour of neural networks, allowing specifications for their building blocks to be readily obtained. Starting with the derivation of a specification and ending with its hardware implementation, analog hard-wired, feed-forward neural networks with on-chip back-propagation learning are designed in their entirety. On-chip learning is necessary in circumstances where fixed weight configurations cannot be used. It is also useful for the elimination of most mis-matches and parameter tolerances that occur in hard-wired neural network chips. Fully analog neural networks have several advantages over other implementations: low chip area, low power consumption, and high speed operation. Feed-Forward Neural Networks is an excellent source of reference and may be used as a text for advanced courses. Books, Technology, Engineering and Agriculture~~Electronicsl and Communications Engineering~~Electronics Engineering, Feed-Forward Neural Networks~~Book~~9780792395676~~Jouke Annema, , , , , , , , , ,, [PU: Kluwer Academic Publishers]
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Jouke Annema, Jouke Annema:
Feed-Forward Neural Networks: Vector Decomposition Analysis, Modelling and Analog Implementation - new bookISBN: 9780792395676
ID: 978079239567
Feed-Forward Neural Networks: Vector Decomposition Analysis, Modelling and Analog Implementation presents a novel method for the mathematical analysis of neural networks that learn according to the back-propagation algorithm. The book also discusses some other recent alternative algorithms for hardware implemented perception-like neural networks. The method permits a simple analysis of the learning behaviour of neural networks, allowing specifications for their building blocks to be readily obtained. Starting with the derivation of a specification and ending with its hardware implementation, analog hard-wired, feed-forward neural networks with on-chip back-propagation learning are designed in their entirety. On-chip learning is necessary in circumstances where fixed weight configurations cannot be used. It is also useful for the elimination of most mis-matches and parameter tolerances that occur in hard-wired neural network chips. Fully analog neural networks have several advantages over other implementations: low chip area, low power consumption, and high speed operation. Feed-Forward Neural Networks is an excellent source of reference and may be used as a text for advanced courses. Jouke Annema, Jouke Annema, Books, Science and Nature, Feed-Forward Neural Networks: Vector Decomposition Analysis, Modelling and Analog Implementation Books>Science and Nature, Springer
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ISBN: 9780792395676
ID: 15fc953f4c4285628f19b670ec5d2751
Vector Decomposition Analysis, Modelling and Analog Implementation Feed-Forward Neural Networks: Vector Decomposition Analysis, Modelling and Analog Implementation presents a novel method for the mathematical analysis of neural networks that learn according to the back-propagation algorithm. The book also discusses some other recent alternative algorithms for hardware implemented perception-like neural networks. The method permits a simple analysis of the learning behaviour of neural networks, allowing specifications for their building blocks to be readily obtained. Starting with the derivation of a specification and ending with its hardware implementation, analog hard-wired, feed-forward neural networks with on-chip back-propagation learning are designed in their entirety. On-chip learning is necessary in circumstances where fixed weight configurations cannot be used. It is also useful for the elimination of most mis-matches and parameter tolerances that occur in hard-wired neural network chips. Fully analog neural networks have several advantages over other implementations: low chip area, low power consumption, and high speed operation. Feed-Forward Neural Networks is an excellent source of reference and may be used as a text for advanced courses. Bücher / Fremdsprachige Bücher / Englische Bücher 978-0-7923-9567-6, Springer
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ISBN: 9780792395676
ID: 107766011
Feed-Forward Neural Networks: Vector Decomposition Analysis, Modelling and Analog Implementation presents a novel method for the mathematical analysis of neural networks that learn according to the back-propagation algorithm. The book also discusses some other recent alternative algorithms for hardware implemented perception-like neural networks. The method permits a simple analysis of the learning behaviour of neural networks, allowing specifications for their building blocks to be readily obtained. Starting with the derivation of a specification and ending with its hardware implementation, analog hard-wired, feed-forward neural networks with on-chip back-propagation learning are designed in their entirety. On-chip learning is necessary in circumstances where fixed weight configurations cannot be used. It is also useful for the elimination of most mis-matches and parameter tolerances that occur in hard-wired neural network chips. Fully analog neural networks have several advantages over other implementations: low chip area, low power consumption, and high speed operation. Feed-Forward Neural Networks is an excellent source of reference and may be used as a text for advanced courses. Vector Decomposition Analysis, Modelling and Analog Implementation Buch (fremdspr.) Bücher>Fremdsprachige Bücher>Englische Bücher, Springer
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Feed-Forward Neural Networks: Vector Decomposition Analysis, Modelling and Analog Implementation (The Kluwer International Series in Engineering and Computer Science) - hardcover
1995, ISBN: 0792395670
ID: 1276239992
[EAN: 9780792395676], Gebraucht, guter Zustand, [PU: Kluwer], COMPUTER SCIENCE, 238 pp., Hardcover, ex library, else text clean and binding tight
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Title: | Feed-Forward Neural Networks |
ISBN: | 9780792395676 |
Details of the book - Feed-Forward Neural Networks
EAN (ISBN-13): 9780792395676
ISBN (ISBN-10): 0792395670
Hardcover
Publishing year: 1995
Publisher: Springer-Verlag GmbH
256 Pages
Weight: 0,549 kg
Language: eng/Englisch
Book in our database since 08.11.2007 13:45:52
Book found last time on 25.06.2016 10:58:21
ISBN/EAN: 9780792395676
ISBN - alternate spelling:
0-7923-9567-0, 978-0-7923-9567-6
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