A Brief Introduction to Neural Networks
This book provides a comprehensive overview of the subject of neural networks.
Tag(s): Neural Networks
Publication date: 31 Dec 2007
ISBN-10: n/a
ISBN-13: n/a
Paperback: 244 pages
Views: 13,062
Type: N/A
Publisher: n/a
License: Creative Commons Attribution-NoDerivs 3.0 Unported
Post time: 22 May 2016 12:00:00
A Brief Introduction to Neural Networks
This book provides a comprehensive overview of the subject of neural networks.
Publication date: 31 Dec 2007
ISBN-10: n/a
ISBN-13: n/a
Paperback: 244 pages
Views: 13,062
Document Type: N/A
Publisher: n/a
License: Creative Commons Attribution-NoDerivs 3.0 Unported
Post time: 22 May 2016 12:00:00
Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
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Neural networks are a bio-inspired mechanism of data processing, that enables computers to learn technically similar to a brain and even generalize once solutions to enough problem instances are tought.
Table of Contents:
Introduction, motivation and history - Biological neural networks - Components of artificial neural networks (fundamental) - Fundamentals on learning and training samples (fundamental) - The perceptron, backpropagation and its variants - Radial basis functions - Recurrent perceptron-like networks - Hopfield networks - Learning vector quantization - Self-organizing feature maps - Adaptive resonance theory - Excursus: Cluster analysis and regional and online learnable fields - Excursus: neural networks used for prediction - Excursus: reinforcement learning
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About The Author(s)
David Kriesel is Product Manager Business Analytics at IVU Traffic Technologies AG and work on topics in the Area of DataScience and Predictive Analytics.
David Kriesel is Product Manager Business Analytics at IVU Traffic Technologies AG and work on topics in the Area of DataScience and Predictive Analytics.