Pattern Recognition with Neural Networks in C++

The addition of artificial network computing to traditional pattern recognition has given rise to a new, different, and more powerful methodology that is presented in this practical guide to the application of artificial neural networks. The material covered in the book is accessible to working engineers with little or no explicit background in neural networks.

List of contents

1. Introduction 2. Neural Networks: An Overview 3. Preprocessing 4. Feed-Forward Networks with Supervised Learning 5. Some Other Types of Neural Networks 6. Feature Extraction I: Geometric Features and Transformations 7. Feature Extraction II: Principal Component Analysis 8. Kohonen Networks and Learning Vector Quantization 9. Neural Associative Memories and Hopfield Networks 10. Adaptive Resonance Theory (ART) 11. Neocognitron 12. Systems with Multiple Classifiers

About the author

Pandya\, Abhijit S.; Macy\, Robert B.

Summary

This book is a practical guide to the methods of application of artificial neural networks to pattern recognition in C++. It provides an intuitive explanation of each method for each network paradigm, supported by a rigorous mathematical approach where necessary.

Product details

• Authors: Robert B. Macy, Macy Robert B., Abhijit S. Pandya, Pandya Abhijit S.
• Publisher: Taylor and Francis
• Languages: English
• Product format: Hardback
• Released: 17.10.1995
• EAN: 9780849394621
• ISBN: 978-0-8493-9462-1
• No. of pages: 426
• Weight: 1020 g
• Illustrations: Tabellen, schwarz-weiss
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > Application software; COMPUTERS / Optical Data Processing, pattern recognition, Programming & scripting languages: general, Programming and scripting languages: general, COMPUTERS / Data Science / Neural Networks, COMPUTERS / Languages / General, Neural networks and fuzzy systems, Neural networks & fuzzy systems