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.
"synopsis" may belong to another edition of this title.
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).
A survey of the philosophical implications and practical applications of fuzzy systems
Fuzzy mathematical concepts such as fuzzy sets, fuzzy logic, and similarity relations represent one of the most exciting currents in modern engineering and have great potential in applications ranging from control theory to bioinformatics. Data Engineering guides the reader through a number of concepts interconnected by fuzzy mathematics and discusses these concepts from a systems engineering perspective to showcase the continuing vitality, attractiveness, and applicability of fuzzy mathematics.
The author discusses the fundamental aspects of data analysis, systems modeling, and uncertainty calculi. He avoids a narrow discussion of specialized methodologies and takes a holistic view of the nature and application of fuzzy systems, considering principles, paradigms, and methodologies along the way. This broad coverage includes:
* Fundamentals of modeling, identification, and clustering
* System analysis
* Uncertainty techniques
* Random-set modeling and identification
* Fuzzy inference engines
* Fuzzy classification, control, and mathematics
In the important emerging field of bioinformatics, the book sets out how to encode a natural system in mathematical models, describes methods to identify interrelationships and interactions from data, and thereby helps the practitioner to decide which variables to measure and why.
Data Engineering serves as an up-to-date and informative survey of the theoretical and practical tools for analyzing complex systems. It offers a unique treatment of complex issues that is accessible to students and researchers from a variety of backgrounds.
A survey of the philosophical implications and practical applications of fuzzy systems
Fuzzy mathematical concepts such as fuzzy sets, fuzzy logic, and similarity relations represent one of the most exciting currents in modern engineering and have great potential in applications ranging from control theory to bioinformatics. Data Engineering guides the reader through a number of concepts interconnected by fuzzy mathematics and discusses these concepts from a systems engineering perspective to showcase the continuing vitality, attractiveness, and applicability of fuzzy mathematics.
The author discusses the fundamental aspects of data analysis, systems modeling, and uncertainty calculi. He avoids a narrow discussion of specialized methodologies and takes a holistic view of the nature and application of fuzzy systems, considering principles, paradigms, and methodologies along the way. This broad coverage includes:
* Fundamentals of modeling, identification, and clustering
* System analysis
* Uncertainty techniques
* Random-set modeling and identification
* Fuzzy inference engines
* Fuzzy classification, control, and mathematics
In the important emerging field of bioinformatics, the book sets out how to encode a natural system in mathematical models, describes methods to identify interrelationships and interactions from data, and thereby helps the practitioner to decide which variables to measure and why.
Data Engineering serves as an up-to-date and informative survey of the theoretical and practical tools for analyzing complex systems. It offers a unique treatment of complex issues that is accessible to students and researchers from a variety of backgrounds.
"About this title" may belong to another edition of this title.
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Hardcover. Condition: new. Hardcover. 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. There are many situations in science and engineering where complex output data from a given system is used to formulate a model of how that system operates, or to simulate its response to different inputs. Applications include control, decision theory, and the emerging fields of bioinformatics. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780471416562
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