Contributions

  • Obradovic, Dragan. - Contributor

Publication

1996 - Springer, New York, New York (State)

Language

English

Word Count

65,250 words, Guess

Page Count

261 pages

Identifiers

  • ISBN-100387946667
  • ISBN-139780387946665
  • Goodreads3422894
  • Library of Congress Control Number95048306
  • Open LibraryOL811391M

Classifications

  • DDC006.3
  • LCCQA76.87 .D47 1996

Description

Neural networks provide a powerful new technology to model and control nonlinear and complex systems. In this book, the authors present a detailed formulation of neural networks from the information-theoretic viewpoint. They show how this perspective provides new insights into the design theory of neural networks. In particular, they show how these methods may be applied to the topics of supervised and unsupervised learning, including feature extraction, linear and nonlinear independent component analysis, and Boltzmann machines. Readers are assumed to have a basic understanding of neural networks, but all of the relevant concepts from information theory are carefully introduced and explained. Consequently, readers from several different scientific disciplines - notably, cognitive scientists, engineers, physicists, statisticians, and computer scientists - will find this book to be a very valuable contribution to this topic.

Subjects

Series Statement

  • Perspectives in neural computing

Other Editions

  • An information-theoretic approach to neural computingSpringer1996-01-01

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