Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
Direct and inverse problem in comparison of fuzzy data
Fuzzy Sets and Systems
Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Fuzzy pattern classification and the connectionist approach
Pattern Recognition Letters - Special issue on fuzzy set technology in pattern recognition
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In this paper we will deal with the problem of classification and interpretation of electrocardiograms (ECG) in the presence of uncertain environment. The problem can be conveniently handled in a general framework of pattern recognition. Uncertainty that is evident there relates both to (i) a perception perspective established in the classification process as well as (ii) final class assignment. Due to this type of uncertainty which essentially derives from a lack of sharp boundaries (i.e. precise definitions) of the features of the signal and the partial class membership (that is characteristic for unclear, borderline cases) of individual signals a methodology of fuzzy set theory is appropriate. Within this framework it will be clarified how all perception properties concerning signal processing and its interpretation can be handled.