Data Engineering
Fuzzy Mathematics in Systems Theory and Data Analysis
Published on 24. March 2004
296 pages
978-0-471-46410-5 (ISBN)
Description
Although data engineering is a multi-disciplinary field withapplications in control, decision theory, and the emerging hot areaof bioinformatics, there are no books on the market that make thesubject accessible to non-experts. This book fills the gap in thefield, offering a clear, user-friendly introduction to the maintheoretical and practical tools for analyzing complex systems. Anftp site features the corresponding MATLAB and Mathematical toolsand simulations.
Market: Researchers in data management, electrical engineering,computer science, and life sciences.
Reviews / Votes
"To cope with real world uncertainties and provide a philosophicaland practical guide...several methodologies are presented..."(SciTech Book News, Vol. 25, No. 4, December 2001) "...certainly a book that should be in the library of anyinstitution where research and advanced study in fuzzy systems arecarried out." (Choice, Vol. 39, No. 7, March 2002) "...well organized, easy to read, and self-contained.... I wouldrecommend it to anyone interested in self-study of the basic ideasof fuzzy systems..." (International Journal of GeneralSystems, Vol. 31, No. 6, 2002)More details
Other editions
Additional editions
Software
03/2002
Wiley
€171.88
Shipment within 10-20 days
Book
07/2001
Wiley
€174.50
Shipment within 10-20 days
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.
