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Feed-Forward Neural Networks
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Feed-Forward Neural Networks - new book

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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Feed-Forward Neural Networks: Vector Decomposition Analysis, Modelling and Analog Implementation (Hardback) - Jouke Annema
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Jouke Annema:

Feed-Forward Neural Networks: Vector Decomposition Analysis, Modelling and Analog Implementation (Hardback) - hardcover

1995, ISBN: 0792395670

ID: 11220955317

[EAN: 9780792395676], Neubuch, [PU: Kluwer Academic Publishers, United States], Technology|Electricity, Technology|Electronics|Circuits|General, Technology|Engineering|Electrical, Computers & the Internet|Neural Networks, Computers & the Internet|Programming|General, Language: English . Brand New Book ***** Print on Demand *****. 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.

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Feed-Forward Neural Networks: Vector Decomposition Analysis, Modelling and Analog Implementation (Hardback) - Jouke Annema
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Jouke Annema:
Feed-Forward Neural Networks: Vector Decomposition Analysis, Modelling and Analog Implementation (Hardback) - hardcover

1995

ISBN: 0792395670

ID: 3119748153

[EAN: 9780792395676], Neubuch, [PU: Kluwer Academic Publishers, United States], Technology|Electricity, Technology|Electronics|Circuits|General, Technology|Engineering|Electrical, Computers & the Internet|Neural Networks, Computers & the Internet|Programming|General, Language: English . Brand New Book ***** Print on Demand *****.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.

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Feed-Forward Neural Networks - Jouke Annema
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Jouke Annema:
Feed-Forward Neural Networks - new book

ISBN: 9780792395676

ID: 698101599

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 Bücher > Fremdsprachige Bücher > Englische Bücher gebundene Ausgabe 31.05.1995 Buch (fremdspr.), Springer, .199

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Annema, Jouke: Feed-Forward Neural Networks
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ISBN: 9780792395676

ID: 185407666

Vector Decomposition Analysis, Modelling and Analog Implementation. 1995. Auflage Vector Decomposition Analysis, Modelling and Analog Implementation. 1995. Auflage Bücher > Wissenschaft > Technik, [PU: Kluwer Academic Publishers]

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Details of the book
Feed-Forward Neural Networks
Author:

Annema, Jouke

Title:

Feed-Forward Neural Networks

ISBN:

0792395670

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.

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 25.03.2017 14:09:41
ISBN/EAN: 0792395670

ISBN - alternate spelling:
0-7923-9567-0, 978-0-7923-9567-6

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