DocumentCode
3123238
Title
Non-monotone averaging aggregation
Author
Beliakov, Gleb ; Yu, Shui ; Paternain, Daniel
Author_Institution
Sch. of Inf. Technol., Deakin Univ., Melbourne, VIC, Australia
fYear
2011
fDate
27-30 June 2011
Firstpage
2905
Lastpage
2908
Abstract
We advance the theory of aggregation operators and introduce non-monotone aggregation methods based on minimization of a penalty for inputs disagreements. The application in mind is processing data sets which may contain noisy values. Our aim is to filter out noise while at the same time preserve signs of unusual values. We review various methods of robust estimators of location, and then introduce a new estimator based on penalty minimisation.
Keywords
fuzzy set theory; minimisation; aggregation operators; data sets processing; noise filter; non monotone averaging aggregation; penalty minimisation; robust estimators; Cognition; Fuzzy systems; Least squares approximation; Minimization; Noise; Optimization; Robustness; Aggregation operator; estimators of location; outliers; penalty function;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems (FUZZ), 2011 IEEE International Conference on
Conference_Location
Taipei
ISSN
1098-7584
Print_ISBN
978-1-4244-7315-1
Electronic_ISBN
1098-7584
Type
conf
DOI
10.1109/FUZZY.2011.6007643
Filename
6007643
Link To Document