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FPGA Implementations of Neural Networks

  • Book
  • © 2006

Overview

Editors:
  1. Amos R. Omondi

    1. Flinders University, Adelaide, Australia

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  2. Jagath C. Rajapakse

    1. Nanyang Tecnological University, Singapore

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    You can also search for this editor in PubMed   Google Scholar

  • There is no present book addressing the subject of FPGA implementation of neurocomputers
  • The book provides an extensive coverage of the topic
  • The research issues addressed in the book are hot research topics
  • Includes supplementary material: sn.pub/extras

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Table of contents (12 chapters)

  1. Front Matter

    Pages i-xii
    Download chapter PDF

  2. FPGA Neurocomputers

    • Amos R. Omondi, Jagath C. Rajapakse, Mariusz Bajger
    Pages 1-36

  3. On the Arithmetic Precision for Implementing Back-Propagation Networks on FPGA: A Case Study

    • Medhat Moussa, Shawki Areibi, Kristian Nichols
    Pages 37-61

  4. FPNA: Concepts and Properties

    • Bernard Girau
    Pages 63-101

  5. FPNA: Applications and Implementations

    • Bernard Girau
    Pages 103-136

  6. Back-Propagation Algorithm Achieving 5 Gops on the Virtex-E

    • Kolin Paul, Sanjay Rajopadhye
    Pages 137-165

  7. FPGA Implementation of Very Large Associative Memories

    • Dan Hammerstrom, Changjian Gao, Shaojuan Zhu, Mike Butts
    Pages 167-195

  8. FPGA Implementations of Neocognitrons

    • Alessandro Noriaki Ide, José Hiroki Saito
    Pages 197-224

  9. Self Organizing Feature Map for Color Quantization on FPGA

    • Chip-Hong Chang, Menon Shibu, Rui Xiao
    Pages 225-245

  10. Implementation of Self-Organizing Feature Maps in Reconfigurable Hardware

    • Mario Porrmann, Ulf Witkowski, Ulrich Rückert
    Pages 247-269

  11. FPGA Implementation of a Fully and Partially Connected MLP

    • Antonio Canas, Eva M. Ortigosa, Eduardo Ros, Pilar M. Ortigosa
    Pages 271-296

  12. FPGA Implementation of Non-Linear Predictors

    • Rafael Gadea-Girones, Agustn Ramrez-Agundis
    Pages 297-323

  13. The REMAP Reconfigurable Architecture: A Retrospective

    • Lars Bengtsson, Arne Linde, Tomas Nordstrom, Bertil Svensson, Mikael Taveniku
    Pages 325-360
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Keywords

About this book

During the 1980s and early 1990s there was signi?cant work in the design and implementation of hardware neurocomputers. Nevertheless, most of these efforts may be judged to have been unsuccessful: at no time have have ha- ware neurocomputers been in wide use. This lack of success may be largely attributed to the fact that earlier work was almost entirely aimed at developing custom neurocomputers, based on ASIC technology, but for such niche - eas this technology was never suf?ciently developed or competitive enough to justify large-scale adoption. On the other hand, gate-arrays of the period m- tioned were never large enough nor fast enough for serious arti?cial-neur- network (ANN) applications. But technology has now improved: the capacity and performance of current FPGAs are such that they present a much more realistic alternative. Consequently neurocomputers based on FPGAs are now a much more practical proposition than they have been in the past. This book summarizes some work towards this goal and consists of 12 papers that were selected, after review, from a number of submissions. The book is nominally divided into three parts: Chapters 1 through 4 deal with foundational issues; Chapters 5 through 11 deal with a variety of implementations; and Chapter 12 looks at the lessons learned from a large-scale project and also reconsiders design issues in light of current and future technology.

Editors and Affiliations

  • Flinders University, Adelaide, Australia

    Amos R. Omondi

  • Nanyang Tecnological University, Singapore

    Jagath C. Rajapakse

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