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Pattern Recognition with Fuzzy Objective Function Algorithms

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References
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Journal ArticleDOI

On pattern classification algorithms--Introduction and survey

TL;DR: It is shown that these algorithms can be classified according to the type of input information required and that the techniques of estimation, decision, and optimization theory can be used effectively to derive known as well as new results.
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Convex decompositions of fuzzy partitions

TL;DR: It is shown how the sequence of partitions in any convex decomposition leads to a matrix for which the norm of the corresponding coefficient vector equals a scalar measure of partition fuzziness used with certain fuzzy clustering algorithms.
Book ChapterDOI

A Category-Theoretic Approach to Systems in a Fuzzy World

TL;DR: The last 30 years have seen the growth of a new branch of mathematics called category theory which provides a general perspective on many different branches of mathematics as discussed by the authors, and many workers (see Lawvere, 1972) have argued that it is category theory, rather than Set Theory, that provides the proper setting for the study of the Foundations of Mathematics.
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Numerical classification for taxonomic problems

TL;DR: A new procedure for numerical classification has been developed to aid in biological classification problems, particularly at the infraspecific level or lower, and appears to be consistent with the classification methods employed by most taxonomists.