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Feed-Forward Neural Networks: Vector Decomposition Analysis, Modelling and Analog Implementation

by Jouke Annema
Save 35% Save 35%
Current price ₹7,267.00
Original price ₹11,179.00
Original price ₹11,179.00
Original price ₹11,179.00
(-35%)
₹7,267.00
Current price ₹7,267.00

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Book cover type: Paperback
  • ISBN13: 9781461359906
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Springer
  • Publisher Imprint: Springer
  • Publication Date:
  • Pages: 238
  • Original Price: EUR 99.99
  • Language: English
  • Edition: Softcover Repri
  • Item Weight: 392 grams
  • BISAC Subject(s): Electronics / Circuits / General, Electrical, and Physics / Mathematical & Computational

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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