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Neural Networks and Micromechanics

By Ernst Kussul , Tatiana Baidyk , Donald C. Wunsch

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This text covers a field of research involving the use of neural network techniques for image recognition to tasks in the area of micromechanics. It includes theoretical analysis, details of machine tool prototypes, and results from various experiments.

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  • ISBN13: 978-3-6420-2534-1
  • 232 Pages
  • User Level: Science
  • Publication Date: December 1, 2009
  • Available eBook Formats: PDF
Full Description
This is an interdisciplinary field of research involving the use of neural network techniques for image recognition applied to tasks in the area of micromechanics. The book is organized into chapters on classic neural networks and novel neural classifiers; recognition of textures and object forms; micromechanics; and adaptive algorithms with neural and image recognition applications. The authors include theoretical analysis of the proposed approach, they describe their machine tool prototypes in detail, and they present results from experiments involving microassembly, and handwriting and face recognition. This book will benefit scientists, researchers and students working in artificial intelligence, particularly in the fields of image recognition and neural networks, and practitioners in the area of microengineering.
Table of Contents

Table of Contents

  1. Introduction.
  2. Classical Neural Networks.
  3. Neural Classifiers.
  4. A Permutation Coding Technique for an Image Recognition System.
  5. Associative
  6. Projective Neural Networks.
  7. Recognition of Textures, Object Shapes and Handwritten Words.
  8. Hardware for Neural Networks.
  9. Micromechanics.
  10. Applications of Neural Networks in Micromechanics.
  11. Texture Recognition in Micromechanics.
  12. Adaptive Algorithms Based on Technical Vision.
  13. Conclusions.
  14. References.

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