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Studies in Computational Intelligence

Neural Networks: Computational Models and Applications

Authors: Tang, Huajin, Tan, Kay Chen, Yi, Zhang

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eBook $169.00
price for USA in USD (gross)
  • ISBN 978-3-540-69226-3
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Hardcover $219.99
price for USA in USD
  • ISBN 978-3-540-69225-6
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  • Usually dispatched within 3 to 5 business days.
Softcover $239.00
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  • ISBN 978-3-642-08871-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

Neural Networks: Computational Models and Applications covers a wealth of important theoretical and practical issues in neural networks, including the learning algorithms of feed-forward neural networks, various dynamical properties of recurrent neural networks, winner-take-all networks and their applications in broad manifolds of computational intelligence: pattern recognition, uniform approximation, constrained optimization, NP-hard problems, and image segmentation. By presenting various computational models, this book is developed to provide readers with a quick but insightful understanding of the broad and rapidly growing areas in the neural networks domain.

Besides laying down fundamentals on artificial neural networks, this book also studies biologically inspired neural networks. Some typical computational models are discussed, and subsequently applied to objection recognition, scene analysis and associative memory. The studies of bio-inspired models have important implications in computer vision and robotic navigation, as well as new efficient algorithms for image analysis. Another significant feature of the book is that it begins with fundamental dynamical problems in presenting the mathematical techniques extensively used in analyzing neurodynamics, thus allowing non-mathematicians to develop and apply these analytical techniques easily.

Written for a wide readership, engineers, computer scientists and mathematicians interested in machine learning, data mining and neural networks modeling will find this book of value. This book will also act as a helpful reference for graduate students studying neural networks and complex dynamical systems.

Table of contents (17 chapters)

  • Introduction

    Pages 1-7

  • Feedforward Neural Networks and Training Methods

    Pages 9-21

  • New Dynamical Optimal Learning for Linear Multilayer FNN

    Pages 23-34

  • Fundamentals of Dynamic Systems

    Pages 35-56

  • Various Computational Models and Applications

    Pages 57-79

Buy this book

eBook $169.00
price for USA in USD (gross)
  • ISBN 978-3-540-69226-3
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $219.99
price for USA in USD
  • ISBN 978-3-540-69225-6
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $239.00
price for USA in USD
  • ISBN 978-3-642-08871-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Neural Networks: Computational Models and Applications
Authors
Series Title
Studies in Computational Intelligence
Series Volume
53
Copyright
2007
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag Berlin Heidelberg
eBook ISBN
978-3-540-69226-3
DOI
10.1007/978-3-540-69226-3
Hardcover ISBN
978-3-540-69225-6
Softcover ISBN
978-3-642-08871-1
Series ISSN
1860-949X
Edition Number
1
Number of Pages
XXII, 300
Number of Illustrations and Tables
103 b/w illustrations
Topics