Skip to main content
SpringerLink
Log in

Neural Networks in Multidimensional Domains

Fundamentals and New Trends in Modelling and Control

  • Book
  • © 1998

Overview

Editors:
  1. Paolo Arena
    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  2. Luigi Fortuna
    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  3. Giovanni Muscato
    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  4. Maria Gabriella Xibilia
    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  • The first argument of its kind to be published
  • Has multidisciplinary appeal for students in related areas
  • The content, layout and price are ideal for graduates and students

Part of the book series: Lecture Notes in Control and Information Sciences (LNCIS, volume 234)

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (7 chapters)

  1. Front Matter

    Download chapter PDF

  2. Introduction to MLP neural networks

    Pages 3-11

  3. Neural networks in complex algebra

    Pages 13-35

  4. Vectorial neural networks

    Pages 37-42

  5. Quaternion algebra

    Pages 43-47

  6. MLP in quaternion algebra

    Pages 49-75

  7. Chaotic time series prediction with CMLP and HMLP

    Pages 77-98

  8. Applications of quaternions in robotics

    Pages 99-111

  9. Back Matter

    Download chapter PDF
Back to top

Keywords

About this book

In this monograph, new structures of neural networks in multidimensional domains are introduced. These architectures are a generalization of the Multi-layer Perceptron (MLP) in Complex, Vectorial and Hypercomplex algebra. The approximation capabilities of these networks and their learning algorithms are discussed in a multidimensional context. The work includes the theoretical basis to address the properties of such structures and the advantages introduced in system modelling, function approximation and control. Some applications, referring to attractive themes in system engineering and a MATLAB software tool, are also reported. The appropriate background for this text is a knowledge of neural networks fundamentals. The manuscript is intended as a research report, but a great effort has been performed to make the subject comprehensible to graduate students in computer engineering, control engineering, computer sciences and related disciplines.

Bibliographic Information

  • Book Title: Neural Networks in Multidimensional Domains

  • Book Subtitle: Fundamentals and New Trends in Modelling and Control

  • Editors: Paolo Arena, Luigi Fortuna, Giovanni Muscato, Maria Gabriella Xibilia

  • Series Title: Lecture Notes in Control and Information Sciences

  • DOI: https://doi.org/10.1007/BFb0047683

  • Publisher: Springer London

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer-Verlag London 1998

  • Softcover ISBN: 978-1-85233-006-4Published: 28 April 1998

  • eBook ISBN: 978-1-84628-527-1Published: 11 April 2006

  • Series ISSN: 0170-8643

  • Series E-ISSN: 1610-7411

  • Edition Number: 1

  • Number of Pages: XIV, 169

  • Number of Illustrations: 7 b/w illustrations

  • Topics: Control and Systems Theory

Publish with us

Policies and ethics

Back to top

Search

Navigation