FPGA Implementations of Neural Networks

  • Amos R. Omondi
  • Jagath C. Rajapakse

Table of contents

  1. Front Matter
    Pages i-xii
  2. Amos R. Omondi, Jagath C. Rajapakse, Mariusz Bajger
    Pages 1-36
  3. Bernard Girau
    Pages 63-101
  4. Bernard Girau
    Pages 103-136
  5. Kolin Paul, Sanjay Rajopadhye
    Pages 137-165
  6. Dan Hammerstrom, Changjian Gao, Shaojuan Zhu, Mike Butts
    Pages 167-195
  7. Alessandro Noriaki Ide, José Hiroki Saito
    Pages 197-224
  8. Chip-Hong Chang, Menon Shibu, Rui Xiao
    Pages 225-245
  9. Mario Porrmann, Ulf Witkowski, Ulrich Rückert
    Pages 247-269
  10. Antonio Canas, Eva M. Ortigosa, Eduardo Ros, Pilar M. Ortigosa
    Pages 271-296
  11. Rafael Gadea-Girones, Agustn Ramrez-Agundis
    Pages 297-323
  12. Lars Bengtsson, Arne Linde, Tomas Nordstrom, Bertil Svensson, Mikael Taveniku
    Pages 325-360

About this book

Introduction

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.

Keywords

Consumer Electronics Performance Text algorithms artificial intelligence integrated circuit metal-oxide-semiconductor transistor static-induction transistor tools

Editors and affiliations

  • Amos R. Omondi
    • 1
  • Jagath C. Rajapakse
    • 2
  1. 1.Flinders UniversityAdelaideAustralia
  2. 2.Nanyang Tecnological UniversitySingapore

Bibliographic information

  • DOI https://doi.org/10.1007/0-387-28487-7
  • Copyright Information Springer 2006
  • Publisher Name Springer, Boston, MA
  • eBook Packages Engineering
  • Print ISBN 978-0-387-28485-9
  • Online ISBN 978-0-387-28487-3
  • About this book