By Ketty Georgieva Peeva, Yordan Kostadinov Kyosev
This publication examines fuzzy relational calculus concept with functions in a number of engineering matters. The scope of the textual content covers unified and specific equipment with algorithms for direct and inverse challenge answer in fuzzy relational calculus. wide engineering purposes of fuzzy relation compositions and fuzzy linear platforms (linear, relational and intuitionistic) are mentioned. a few examples of such purposes contain ideas of equivalence, aid and minimization difficulties in fuzzy machines, trend acceptance in fuzzy languages, optimization and inference engines in cloth and chemical engineering, and so forth. A complete evaluation of the authors' unique paintings in fuzzy relational calculus can be supplied in every one bankruptcy. The hooked up CD-Rom includes a toolbox with many services for fuzzy calculations, including an unique set of rules for inverse challenge solution in MATLAB. This publication is usually compatible to be used as a textbook in similar classes at complex undergraduate and graduate degrees.
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Additional resources for Fuzzy Relational Calculus: Theory, Applications And Software
1984), (1989), Drewniak (1989), Higashi and Klir (1984), Klir et al. (1997), Klir and Yuan (1995), Lin et al. (1995), Pappis and Sugeno (1985), Pedrycz (1994), Peeva (1992), (2002b), (2004b), Sanchez (1977a), (1979a), (1986), Stamou and Tzafestas (1999), Wu (1986)]. Other methods for solving fuzzy relational equations are out of the scope of this book and here, for completeness of the exposition, we only announce some fragments on the settlement of the subjects. There exist tasks in which approximate solution instead of exact one is reasonable.
Monographs by [Bezdek (1981), Bezdek and Pal (1992), Bezdek et al. (1999b), Friedman and Kandel (1998), Kandel (1982), Pal and Majumder (1986)] are classics in fuzzy pattern recognition. They cover fuzzy clustering, various applications of fuzzy pattern recognition, the use of fuzzy sets in image processing, fuzzy grammars and their use in syntactic pattern recognition, and numerous applications of the various types of pattern recognition problems. The book edited by Bezdek and Pal  is currently the main resource of information regarding various aspects of fuzzy pattern recognition.
Each category may be characterized by more than one prototypical structure. The classification of objects into categories is the subject of cluster analysis. However, the applicability of cluster analysis is not restricted to pattern recognition. It is applicable, for example, to the construction of taxonomies in biology and other areas, classification of documents in information retrieval, and social groupings based on various criteria. The utility of fuzzy set theory in pattern recognition and cluster analysis was already recognized in the mid-1960s, and the literature dealing with fuzzy pattern recognition and fuzzy clustering is now quite extensive.
Fuzzy Relational Calculus: Theory, Applications And Software by Ketty Georgieva Peeva, Yordan Kostadinov Kyosev