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VLSI - Compatible Implementations for Artificial Neural Networks (Paperback, Softcover reprint of the original 1st ed. 1997) Loot Price: R2,769
Discovery Miles 27 690
VLSI - Compatible Implementations for Artificial Neural Networks (Paperback, Softcover reprint of the original 1st ed. 1997):...

VLSI - Compatible Implementations for Artificial Neural Networks (Paperback, Softcover reprint of the original 1st ed. 1997)

Sied Mehdi Fakhraie, Kenneth C. Smith

Series: The Springer International Series in Engineering and Computer Science, 382

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Loot Price R2,769 Discovery Miles 27 690 | Repayment Terms: R259 pm x 12*

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VLSI-Compatible Implementations for Artificial Neural Networks introduces the basic premise of the authors' approach to biologically-inspired and VLSI-compatible definition, simulation, and implementation of artificial neural networks. In addition, the book develops a set of guidelines for general hardware implementation of ANNs. These guidelines are then used to find solutions for the usual difficulties encountered in any potential work, and as guidelines by which to reach the best compromise when several options exist. Furthermore, system-level consequences of using the proposed techniques in future submicron technologies with almost-linear MOS devices are discussed. While the major emphasis in this book is to develop neural networks optimized for compatibility with their implementation media, the work has also been extended to the design and implementation of a fully-quadratic ANN based on the desire to have network definitions epitomized for both efficient discrimination of closed-boundary circular areas and ease of implementation in a CMOS technology.VLSI-Compatible Implementations for Artificial Neural Networks implements a comprehensive approach which starts with an analytical evaluation of specific artificial networks. This provides a clear geometrical interpretation of the behavior of different variants of these networks. In combination with the guidelines developed towards a better final implementation, these concepts have allowed the authors to conquer various problems encountered and to make effective compromises. Then, to facilitate the investigation of the models needed when more difficult problems must be faced, a custom simulating program for various cases is developed. Finally, in order to demonstrate the authors' findings and expectations, several VLSI integrated circuits have been designed, fabricated, and tested. VLSI-Compatible Implementations for Artificial Neural Networksm> serves as an excellent reference source and may be used as a text for advanced courses on the subject.

General

Imprint: Springer-Verlag New York
Country of origin: United States
Series: The Springer International Series in Engineering and Computer Science, 382
Release date: October 2012
First published: 1997
Authors: Sied Mehdi Fakhraie • Kenneth C. Smith
Dimensions: 235 x 155 x 12mm (L x W x T)
Format: Paperback
Pages: 194
Edition: Softcover reprint of the original 1st ed. 1997
ISBN-13: 978-1-4613-7897-6
Categories: Books > Science & Mathematics > Physics > Thermodynamics & statistical physics > Statistical physics
Books > Professional & Technical > Energy technology & engineering > Electrical engineering > General
Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Circuits & components
LSN: 1-4613-7897-4
Barcode: 9781461378976

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