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Record type:	stať ve sborníku (D)
Home Department:	Ústav pro výzkum a aplikace fuzzy modelování (94410)
Title:	Approximation of Fuzzy Functions by Extended Fuzzy Transforms
Citace	Štěpnička, M. a Lehmke, S. Approximation of Fuzzy Functions by Extended Fuzzy Transforms. In: Fuzzy Days: Computational Intelligence, Theory and Applications (Advances in Soft Computing) 2004 Dortmund. Berlin, Heidelberg, New York: Springer - Verlag, 2005. Springer - Verlag, 2005. s. 187-195. ISBN 3-540-22807-1.

Subtitle
Publication year:	2005
Obor:	Obecná matematika
Number of pages:	9
Page from:	187
Page to:	195
Form of publication:
ISBN code:	3-540-22807-1
ISSN code:
Proceedings title:	Computational Intelligence, Theory and Applications (Advances in Soft Computing)
Proceedings:	Mezinárodní
Publisher name:	Springer - Verlag
Place of publishing:	Berlin, Heidelberg, New York
Country of Publication:
Název konference:	Fuzzy Days
Conference venue:	Dortmund
Datum zahájení konference:
Typ akce podle státní příslušnosti účastníků:	Celosvětová akce
WoS code:	000235172500016
EID:

Key words in English:	Fuzzy sets; Approximation; Fuzzy approximation; Fuzzy transforms; Normal forms; Fuzzy control
Annotation in original language:	A fuzzy approximation method called fuzzy transforms for approximation of continuous function is presented in this paper. It is shown how can be fuzzy transforms naturally generalized for functions with more variables. A fuzzy function as an approximated mapping is considered. This leads to an extension of fuzzy transforms for fuzzy function as well as to an extension of generalized fuzzy transforms for fuzzy functions with more variables. It is shown how the proposed method can be used as so called learning to obtain a fuzzy rule base for fuzzy control.
Annotation in english language:	A fuzzy approximation method called fuzzy transforms for approximation of continuous function is presented in this paper. It is shown how can be fuzzy transforms naturally generalized for functions with more variables. A fuzzy function as an approximated mapping is considered. This leads to an extension of fuzzy transforms for fuzzy function as well as to an extension of generalized fuzzy transforms for fuzzy functions with more variables. It is shown how the proposed method can be used as so called learning to obtain a fuzzy rule base for fuzzy control.

References

Reference

R01:	RIV/61988987:17610/05:A10009X6

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