Multi-Valued and Universal Binary Neurons

Theory, Learning and Applications

  • Igor N. Aizenberg
  • Naum N. Aizenberg
  • Joos Vandewalle

Table of contents

  1. Front Matter
    Pages i-7
  2. Igor N. Aizenberg, Naum N. Aizenberg, Joos Vandewalle
    Pages 9-24
  3. Igor N. Aizenberg, Naum N. Aizenberg, Joos Vandewalle
    Pages 25-80
  4. Igor N. Aizenberg, Naum N. Aizenberg, Joos Vandewalle
    Pages 81-137
  5. Igor N. Aizenberg, Naum N. Aizenberg, Joos Vandewalle
    Pages 139-167
  6. Igor N. Aizenberg, Naum N. Aizenberg, Joos Vandewalle
    Pages 169-218
  7. Igor N. Aizenberg, Naum N. Aizenberg, Joos Vandewalle
    Pages 219-255
  8. Igor N. Aizenberg, Naum N. Aizenberg, Joos Vandewalle
    Pages 257-260
  9. Back Matter
    Pages 261-275

About this book

Introduction

Multi-Valued and Universal Binary Neurons deals with two new types of neurons: multi-valued neurons and universal binary neurons. These neurons are based on complex number arithmetic and are hence much more powerful than the typical neurons used in artificial neural networks. Therefore, networks with such neurons exhibit a broad functionality. They can not only realise threshold input/output maps but can also implement any arbitrary Boolean function. Two learning methods are presented whereby these networks can be trained easily. The broad applicability of these networks is proven by several case studies in different fields of application: image processing, edge detection, image enhancement, super resolution, pattern recognition, face recognition, and prediction. The book is hence partitioned into three almost equally sized parts: a mathematical study of the unique features of these new neurons, learning of networks of such neurons, and application of such neural networks. Most of this work was developed by the first two authors over a period of more than 10 years and was only available in the Russian literature. With this book we present the first comprehensive treatment of this important class of neural networks in the open Western literature.
Multi-Valued and Universal Binary Neurons is intended for anyone with a scholarly interest in neural network theory, applications and learning. It will also be of interest to researchers and practitioners in the fields of image processing, pattern recognition, control and robotics.

Keywords

algorithms artificial neural network cognition control detection image processing knowledge learning learning algorithm logic network neural networks pattern recognition robot robotics

Authors and affiliations

  • Igor N. Aizenberg
    • 1
  • Naum N. Aizenberg
    • 1
  • Joos Vandewalle
    • 2
  1. 1.Neural Networks Technologies Ltd.Israel
  2. 2.Departement Elektrotechniek, ESAT/SISTAKatholieke Universiteit LeuvenBelgium

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4757-3115-6
  • Copyright Information Springer-Verlag US 2000
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4419-4978-3
  • Online ISBN 978-1-4757-3115-6
  • About this book