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VLSI - Compatible Implementations for Artificial Neural Networks, Paperback b...

Description: VLSI - Compatible Implementations for Artificial Neural Networks, Paperback by Fakhraie, Sied Mehdi; Smith, Kenneth C., ISBN 1461378974, ISBN-13 9781461378976, Like New Used, Free shipping in the US This book introduces several state-of-the-art VLSI implementations of artificial neural networks (ANNs). It reviews various hardware approaches to ANN implementations: analog, and pulse-coded. The analog approach is emphasized as the main one taken in the later chapters of th. The area of VLSI implementation of ANNs has been progressing for the last 15 years, but not at the fast pace originally predicted. Several reasons have contributed to the slow progress, with the main one being that VLSI implementation of ANNs is an interdisciplinaly area where only a few researchers, academics and graduate students are willing to venture. The work of Professors Fakhraie and Smith, presented in this book, is a welcome addition to the state-of-the-art and will greatly benefit researchers and students working in this area. Of particular value is the use of experimental results to backup extensive simulations and in-depth modeling. The introduction of a synapse-MOS device is novel. Th applies the concept to a number of applications and guides the reader through more possible applications for future work. I am confident that th will benefit a potentially wide readership. M. I. Elmasry University of Waterloo Waterloo, Ontario Canada Preface Neural Networks (NNs), generally defined as parallel networks that employ a large number of simple processing elements to perform computation in a distributed fashion, have attracted a lot of attention in the past fifty years. As the result. many new discoveries have been made.

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VLSI - Compatible Implementations for Artificial Neural Networks, Paperback b...

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Book Title: VLSI - Compatible Implementations for Artificial Neural Networks

Number of Pages: Xxix, 194 Pages

Publication Name: Vlsi -- Compatible Implementations for Artificial Neural Networks

Language: English

Publisher: Springer

Subject: Electronics / Circuits / General, Electrical, System Theory

Publication Year: 2012

Type: Textbook

Item Weight: 12.5 Oz

Subject Area: Technology & Engineering, Science

Author: Sied Mehdi Fakhraie, Kenneth C. Smith

Item Length: 9.3 in

Item Width: 6.1 in

Series: The Springer International Series in Engineering and Computer Science Ser.

Format: Trade Paperback

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