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Artificial Neural Networks

Learning Algorithms, Performance Evaluation, and Applications

  • N. B. Karayiannis
  • A. N. Venetsanopoulos

Table of contents

  1. Front Matter
    Pages i-xv
  2. N. B. Karayiannis, A. N. Venetsanopoulos
    Pages 1-8
  3. N. B. Karayiannis, A. N. Venetsanopoulos
    Pages 9-85
  4. N. B. Karayiannis, A. N. Venetsanopoulos
    Pages 87-139
  5. N. B. Karayiannis, A. N. Venetsanopoulos
    Pages 141-193
  6. N. B. Karayiannis, A. N. Venetsanopoulos
    Pages 195-218
  7. N. B. Karayiannis, A. N. Venetsanopoulos
    Pages 219-257
  8. N. B. Karayiannis, A. N. Venetsanopoulos
    Pages 259-298
  9. N. B. Karayiannis, A. N. Venetsanopoulos
    Pages 299-315
  10. N. B. Karayiannis, A. N. Venetsanopoulos
    Pages 317-369
  11. N. B. Karayiannis, A. N. Venetsanopoulos
    Pages 371-373
  12. Back Matter
    Pages 375-440

About this book

Introduction

1.1 Overview We are living in a decade recently declared as the "Decade of the Brain". Neuroscientists may soon manage to work out a functional map of the brain, thanks to technologies that open windows on the mind. With the average human brain consisting of 15 billion neurons, roughly equal to the number of stars in our milky way, each receiving signals through as many as 10,000 synapses, it is quite a view. "The brain is the last and greatest biological frontier", says James Weston codiscoverer of DNA, considered to be the most complex piece of biological machinery on earth. After many years of research by neuroanatomists and neurophys­ iologists, the overall organization of the brain is well understood, but many of its detailed neural mechanisms remain to be decoded. In order to understand the functioning of the brain, neurobiologists have taken a bottom-up approach of studying the stimulus-response characteristics of single neurons and networks of neurons, while psy­ chologists have taken a top-down approach of studying brain func­ tions from the cognitive and behavioral level. While these two ap­ proaches are gradually converging, it is generally accepted that it may take another fifty years before we achieve a solid microscopic, intermediate, and macroscopic understanding of brain.

Keywords

algorithms convergence high-order neural network learning algorithm learning scheme neural network architecture neural networks training

Authors and affiliations

  • N. B. Karayiannis
    • 1
  • A. N. Venetsanopoulos
    • 2
  1. 1.University of HoustonUSA
  2. 2.University of TorontoCanada

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4757-4547-4
  • Copyright Information Springer-Verlag US 1993
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4419-5132-8
  • Online ISBN 978-1-4757-4547-4
  • Series Print ISSN 0893-3405
  • Buy this book on publisher's site
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