Access this book
Tax calculation will be finalised at checkout
Other ways to access
About this book
The major ANN architectures are discussed to show their powerful possibilities for empirical data analysis, particularly in situations where other methods seem to fail. Theoretical insight is offered by examining the underlying mathematical principles in a detailed, yet clear and illuminating way. Practical experience is provided by discussing several real-world applications in such areas as control, optimization, pattern recognition, software engineering, robotics, operations research, and CAM.
Keywords
Table of contents (15 chapters)
Bibliographic Information
Book Title: Artificial Neural Networks
Book Subtitle: An Introduction to ANN Theory and Practice
Editors: P. J. Braspenning, F. Thuijsman, A. J. M. M. Weijters
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/BFb0027019
Publisher: Springer Berlin, Heidelberg
-
eBook Packages: Springer Book Archive
Copyright Information: Springer-Verlag Berlin Heidelberg 1995
Softcover ISBN: 978-3-540-59488-8Published: 02 June 1995
eBook ISBN: 978-3-540-49283-2Published: 19 November 2005
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: IX, 299
Topics: Artificial Intelligence, Software Engineering/Programming and Operating Systems, Theory of Computation, Computation by Abstract Devices, Numerical Analysis, Pattern Recognition