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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F05%3A03107160%21RIV06-GA0-21230___
rdf:type
n14:Vysledek skos:Concept
dcterms:description
Není k dispozici Real time system parameter estimation from the set of input-output data is usually solved by the quadratic norm minimization of system equations errors - known as least squares (LS). But measurement errors are also in the data matrix and so it is necessary to use modification known astotal least squares (TLS) or mixed LS and TLS. TLS or mixed LS and TLS problem is usually solved by the SVD decomposition of system matrix. So it is difficult to update the solution when the new data are obtained. In the article the new original method using iterative solution of the least squares based on the rotating systém of coordinates [4] is described. The idea of the method is based on the fact that in some special cases the LS and TLS solutions are identical. Real time system parameter estimation from the set of input-output data is usually solved by the quadratic norm minimization of system equations errors - known as least squares (LS). But measurement errors are also in the data matrix and so it is necessary to use modification known astotal least squares (TLS) or mixed LS and TLS. TLS or mixed LS and TLS problem is usually solved by the SVD decomposition of system matrix. So it is difficult to update the solution when the new data are obtained. In the article the new original method using iterative solution of the least squares based on the rotating systém of coordinates [4] is described. The idea of the method is based on the fact that in some special cases the LS and TLS solutions are identical.
dcterms:title
System Identification Using Mixed Total Least Squares by Rotating the System of Coordinates System Identification Using Mixed Total Least Squares by Rotating the System of Coordinates Není k dispozici
skos:prefLabel
Není k dispozici System Identification Using Mixed Total Least Squares by Rotating the System of Coordinates System Identification Using Mixed Total Least Squares by Rotating the System of Coordinates
skos:notation
RIV/68407700:21230/05:03107160!RIV06-GA0-21230___
n5:aktivita
n19:P
n5:aktivity
P(GD102/03/H116), P(LA 184)
n5:dodaniDat
n6:2006
n5:domaciTvurceVysledku
n9:3021580 n9:4337034 n9:2972468 n9:9981101
n5:druhVysledku
n16:A
n5:duvernostUdaju
n7:S
n5:entitaPredkladatele
n12:predkladatel
n5:idSjednocenehoVysledku
545822
n5:idVysledku
RIV/68407700:21230/05:03107160
n5:jazykVysledku
n13:eng
n5:klicovaSlova
ARX model; Identification; Least squares; Total Least squares
n5:klicoveSlovo
n15:Total%20Least%20squares n15:ARX%20model n15:Identification n15:Least%20squares
n5:kodPristupu
n11:L
n5:kontrolniKodProRIV
[4946F4273012]
n5:mistoVydani
Calgary
n5:nosic
neuvedeno
n5:obor
n18:BC
n5:pocetDomacichTvurcuVysledku
4
n5:pocetTvurcuVysledku
4
n5:projekt
n8:GD102%2F03%2FH116 n8:LA%20184
n5:rokUplatneniVysledku
n6:2005
n5:tvurceVysledku
Pekař, Jaroslav Cepák, Milan Štecha, Jan Pachner, Daniel
n17:isbn
0-88986-474-8
n4:organizacniJednotka
21230