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Neural Networks in Multidimensional Domains

Neural Networks in Multidimensional Domains


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About the 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.


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Product Details
  • ISBN-13: 9781852330064
  • Publisher: Springer
  • Publisher Imprint: Springer
  • Height: 234 mm
  • No of Pages: 169
  • Series Title: Lecture Notes in Control and Information Sciences
  • Sub Title: Fundamentals and New Trends in Modelling and Control
  • Width: 156 mm
  • ISBN-10: 1852330066
  • Publisher Date: 28 Apr 1998
  • Binding: Paperback
  • Language: English
  • Returnable: Y
  • Spine Width: 10 mm
  • Weight: 317 gr


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