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.
Table of 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.
About the author
OLAF WOLKENHAUER, Ph D, 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).
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