
Data Engineering
Fuzzy Mathematics in Systems Theory and Data Analysis
Olaf Wolkenhauer(Author)
Wiley (Publisher)
Published on 20. July 2001
Book
Hardback
XXXII, 264 pages
978-0-471-41656-2 (ISBN)
Description
Although data engineering is a multi-disciplinary field with applications in control, decision theory, and the emerging hot area of bioinformatics, there are no books on the market that make the subject accessible to non-experts. This book fills the gap in the field, offering a clear, user-friendly introduction to the main theoretical and practical tools for analyzing complex systems. An ftp site features the corresponding MATLAB and Mathematical tools and simulations.
Market: Researchers in data management, electrical engineering, computer science, and life sciences.
Reviews / Votes
"To cope with real world uncertainties and provide a philosophical and practical guide.several methodologies are presented." (SciTech Book News, Vol. 25, No. 4, December 2001)More details
Product info
gebunden
Edition
1. Auflage
Language
English
Place of publication
United States
Publishing group
John Wiley & Sons Inc
Target group
College/higher education
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 21 mm
Weight
613 gr
ISBN-13
978-0-471-41656-2 (9780471416562)
Schweitzer Classification
Other editions
Additional editions

E-Book
03/2004
Wiley
€147.99
Available for download
Person
OLAF WOLKENHAUER, PhD, holds degrees from the University of Applied Sciences in Hamburg, Germany and the University of Portsmouth in England and received his doctorate in Control Engineering from the University of Manchester Institute of Science and Technology (UMIST). He currently holds joint lectureships at UMIST in the Department of Biomolecular Sciences and the Department of Electrical Engineering and Electronics (Control Systems Center).
Content
Preface.
Acknowledgments.
Introduction.
System Analysis.
Uncertainty Techniques.
Learning from Data: System Identification.
Propositions as Subsets of the Data Space.
Fuzzy Systems and Identification.
Random-Set Modelling and Identification.
Certain Uncertainty.
Fuzzy Inference Engines.
Fuzzy Classification.
Fuzzy Control.
Fuzzy Mathematics.
Summary.
Appendices.
Index.