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A Study of Impulse Response System Identification
Karlstad University, Faculty of Technology and Science.
Karlstad University, Faculty of Technology and Science.
2007 (English)Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

In system identification, different methods are often classified as parametric or non-parametric methods. For parametric methods, a parametric model of a system is considered and the model parameters are estimated. For non-parametric methods, no parametric model is used and the result of the identification is given as a curve or a function.

One of the non-parametric methods is the impulse response analysis. This approach is dynamic simulation. This thesis introduces a new paradigm for dynamic simulation, called impulse-based simulation. This approach is based on choosing a Dirac function as input, and as a result, the output will be equal to the impulse response. However, a Dirac function cannot be realized in practice, and an approximation has to be used. As a consequence, the output will deviate from the impulse response. Once the impulse response is estimated, a parametric model can be fitted to the estimation.

This thesis aims to determine the parameters in a parametric model from an estimated impulse response. The process of investigating the models is a critical aspect of the project. Correlation analysis is used to obtain the weighting function from the estimates of covariance functions.

Later, a relation formed between the parameters and the estimates (obtained by correlation analysis) in the form of a linear system of equations. Furthermore, simulations are carried out using Monte Carlo for investigating the properties of the two step approach, which involves in correlation analysis to find h-parameters and least squares and total least squares methods to solve for the parameters of the model. In order to evaluate the complete capability of the approach to the noise variation a study of signal to noise ratio and mean, mean square error and variances of the estimated parameters is carried out.

The results of the Monte Carlo study indicate that two-step approach can give rather accurate parameter estimates. In addition, the least squares and total least squares methods give similar results.

Place, publisher, year, edition, pages
2007. , p. 39
Keywords [en]
Impulse Response, System Identification, Monte Carlo, Signal to noise ratio(SNR)
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kau:diva-1069Local ID: ELI-21OAI: oai:DiVA.org:kau-1069DiVA, id: diva2:4839
Subject / course
Electrical Engineering
Presentation
2007-05-31, 15:15
Uppsok
Technology
Supervisors
Examiners
Available from: 2007-08-17 Created: 2007-08-17 Last updated: 2016-04-08

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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More styles
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  • de-DE
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  • Other locale
More languages
Output format
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