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Statements

Subject Item
n2:RIV%2F61989100%3A27510%2F11%3A86079331%21RIV13-MSM-27510___
rdf:type
skos:Concept n8:Vysledek
dcterms:description
Data smoothing is an important step within a data processing allowing one to stress the most important patterns. In literature we can find many different smoothing techniques and filter types. Recently, Holčapek and Tichy (2010, 2011) suggested smoothing filters based on fuzzy transform approach introduced by Perfilieva (2004). For this purpose, a eneralization of the concept of fuzzy partition was suggested and the smoothing filter was defined as a combination of the direct discrete fuzzy transform and a slightly modified inverse continuous fuzzy transform. In this paper we compare the proposed filter with the Nadaraya-Watson estimator. We provide an approximative relation of both filters by an optimal parameter selection. Data smoothing is an important step within a data processing allowing one to stress the most important patterns. In literature we can find many different smoothing techniques and filter types. Recently, Holčapek and Tichy (2010, 2011) suggested smoothing filters based on fuzzy transform approach introduced by Perfilieva (2004). For this purpose, a eneralization of the concept of fuzzy partition was suggested and the smoothing filter was defined as a combination of the direct discrete fuzzy transform and a slightly modified inverse continuous fuzzy transform. In this paper we compare the proposed filter with the Nadaraya-Watson estimator. We provide an approximative relation of both filters by an optimal parameter selection.
dcterms:title
A comparison of smoothing filter based on fuzzy transform and Nadaraya-Watson estimators A comparison of smoothing filter based on fuzzy transform and Nadaraya-Watson estimators
skos:prefLabel
A comparison of smoothing filter based on fuzzy transform and Nadaraya-Watson estimators A comparison of smoothing filter based on fuzzy transform and Nadaraya-Watson estimators
skos:notation
RIV/61989100:27510/11:86079331!RIV13-MSM-27510___
n8:predkladatel
n9:orjk%3A27510
n3:aktivita
n4:S n4:Z
n3:aktivity
S, Z(MSM6198898701)
n3:dodaniDat
n10:2013
n3:domaciTvurceVysledku
n17:3252833
n3:druhVysledku
n18:D
n3:duvernostUdaju
n14:S
n3:entitaPredkladatele
n16:predkladatel
n3:idSjednocenehoVysledku
183701
n3:idVysledku
RIV/61989100:27510/11:86079331
n3:jazykVysledku
n21:eng
n3:klicovaSlova
Fuzzy transform, Nonparametric regression, Nadaraya-Watson es- timator, FT-smoothing filter estimator.
n3:klicoveSlovo
n11:Nonparametric%20regression n11:Fuzzy%20transform n11:FT-smoothing%20filter%20estimator. n11:Nadaraya-Watson%20es-%20timator
n3:kontrolniKodProRIV
[730219F80FC1]
n3:mistoKonaniAkce
Janska Dolina
n3:mistoVydani
Praha
n3:nazevZdroje
29th International Conference on Mathematical Methods in Economics 2011 - part I
n3:obor
n15:BB
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
2
n3:rokUplatneniVysledku
n10:2011
n3:tvurceVysledku
Tichý, Tomáš Holčapek, Michal
n3:typAkce
n19:EUR
n3:wos
000309074600043
n3:zahajeniAkce
2011-09-06+02:00
n3:zamer
n7:MSM6198898701
s:numberOfPages
6
n22:hasPublisher
Professional Publishing
n20:isbn
978-80-7431-058-4
n13:organizacniJednotka
27510