Identification of Weakly Nonlinear Systems Based on Support Vector Machines

Anna Marconato; Andrea Boni; D. Petri; Joannes Schoukens

Identification of Weakly Nonlinear Systems Based on Support Vector Machines

Anna Marconato, Andrea Boni, D. Petri, Joannes Schoukens

Elektriciteit

Onderzoeksoutput: Conference paper

1 Citaat (Scopus)

Samenvatting

In this work we analyze the application of Support Vector Machines for Regression (SVRs) to the problem of identifying weakly nonlinear systems. Examples of simple linear and nonlinear systems are considered, taking into account both non-recursive and recursive models. When defining the SVR estimating function, several kinds of kernels are employed, and the effect on the accuracy performance of reducing the training set size is studied.

Originele taal-2	English
Titel	I2MTC 2009 - International Instrumentation and Measurement Technology Conference Singapore, 5-7 May 2009
Pagina's	122-127
Aantal pagina's	6
Status	Published - 5 mei 2009
Evenement	Unknown - Stockholm, Sweden Duur: 21 sep. 2009 → 25 sep. 2009

Conference

Conference	Unknown
Land/Regio	Sweden
Stad	Stockholm
Periode	21/09/09 → 25/09/09

Citeer dit

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title = "Identification of Weakly Nonlinear Systems Based on Support Vector Machines",

abstract = "In this work we analyze the application of Support Vector Machines for Regression (SVRs) to the problem of identifying weakly nonlinear systems. Examples of simple linear and nonlinear systems are considered, taking into account both non-recursive and recursive models. When defining the SVR estimating function, several kinds of kernels are employed, and the effect on the accuracy performance of reducing the training set size is studied.",

keywords = "Identification, weakly nonlinear systems",

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month = may,

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TY - GEN

T1 - Identification of Weakly Nonlinear Systems Based on Support Vector Machines

AU - Marconato, Anna

AU - Boni, Andrea

AU - Petri, D.

AU - Schoukens, Joannes

PY - 2009/5/5

Y1 - 2009/5/5

N2 - In this work we analyze the application of Support Vector Machines for Regression (SVRs) to the problem of identifying weakly nonlinear systems. Examples of simple linear and nonlinear systems are considered, taking into account both non-recursive and recursive models. When defining the SVR estimating function, several kinds of kernels are employed, and the effect on the accuracy performance of reducing the training set size is studied.

AB - In this work we analyze the application of Support Vector Machines for Regression (SVRs) to the problem of identifying weakly nonlinear systems. Examples of simple linear and nonlinear systems are considered, taking into account both non-recursive and recursive models. When defining the SVR estimating function, several kinds of kernels are employed, and the effect on the accuracy performance of reducing the training set size is studied.

KW - Identification

KW - weakly nonlinear systems

M3 - Conference paper

SN - 978-1-4244-3353-7

SP - 122

EP - 127

BT - I2MTC 2009 - International Instrumentation and Measurement Technology Conference Singapore, 5-7 May 2009

T2 - Finds and Results from the Swedish Cyprus Expedition: A Gender Perspective at the Medelhavsmuseet

Y2 - 21 September 2009 through 25 September 2009

ER -

Identification of Weakly Nonlinear Systems Based on Support Vector Machines

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Conference

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