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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F05%3A03110159%21RIV06-GA0-21230___
rdf:type
n8:Vysledek skos:Concept
dcterms:description
Real time system parameter estimation from the set of input-outputdata is usually solved by the quadratic norm minimization ofsystem equations errors - known as least squares (LS). Butmeasurement errors are also in the data matrix and so it isnecessary to use a modification known as total least squares (TLS)or mixed LS and TLS.Instead of quadratic norm minimization otherp-norms are used, for 1 <= p <= 2. In the article newmethod is described named Total p-norm and Mixedtotal p-norm which is the analog to TLS and mixed LS and TLSmethod in the quadratic case.The goal of the paper is to develop the method and compare a setof parameter estimations of ARX model where each estimation isobtained by minimizing total p-norm (1<= p <= 2). Totalp-norm and mixed total p-norm approach is used when errors are also in data matrix. Není k dispozici Real time system parameter estimation from the set of input-outputdata is usually solved by the quadratic norm minimization ofsystem equations errors - known as least squares (LS). Butmeasurement errors are also in the data matrix and so it isnecessary to use a modification known as total least squares (TLS)or mixed LS and TLS.Instead of quadratic norm minimization otherp-norms are used, for 1 <= p <= 2. In the article newmethod is described named Total p-norm and Mixedtotal p-norm which is the analog to TLS and mixed LS and TLSmethod in the quadratic case.The goal of the paper is to develop the method and compare a setof parameter estimations of ARX model where each estimation isobtained by minimizing total p-norm (1<= p <= 2). Totalp-norm and mixed total p-norm approach is used when errors are also in data matrix.
dcterms:title
System Parameter Estimation using p-norm Minimization System Parameter Estimation using p-norm Minimization Není k dispozici
skos:prefLabel
System Parameter Estimation using p-norm Minimization Není k dispozici System Parameter Estimation using p-norm Minimization
skos:notation
RIV/68407700:21230/05:03110159!RIV06-GA0-21230___
n3:aktivita
n12:P
n3:aktivity
P(GD102/03/H116), P(LA 184)
n3:dodaniDat
n4:2006
n3:domaciTvurceVysledku
n10:4337034 n10:9981101 n10:3021580 n10:2972468
n3:druhVysledku
n7:A
n3:duvernostUdaju
n15:S
n3:entitaPredkladatele
n17:predkladatel
n3:idSjednocenehoVysledku
545850
n3:idVysledku
RIV/68407700:21230/05:03110159
n3:jazykVysledku
n5:eng
n3:klicovaSlova
ARX model; Estimation; Identification; Least Squares; Total Least Squares; p-norm
n3:klicoveSlovo
n9:ARX%20model n9:Least%20Squares n9:Identification n9:p-norm n9:Estimation n9:Total%20Least%20Squares
n3:kodPristupu
n18:L
n3:kontrolniKodProRIV
[9F7978C5F4BA]
n3:mistoVydani
Praha
n3:nosic
neuvedeno
n3:obor
n11:BC
n3:pocetDomacichTvurcuVysledku
4
n3:pocetTvurcuVysledku
4
n3:projekt
n13:LA%20184 n13:GD102%2F03%2FH116
n3:rokUplatneniVysledku
n4:2005
n3:tvurceVysledku
Pekař, Jaroslav Cepák, Milan Štecha, Jan Pachner, Daniel
n16:organizacniJednotka
21230