An analysis of the parametrization by data driven local coordinates for multivariable linear systems |
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Authors: | Thomas Ribarits [Author Vitae] Manfred Deistler [Author Vitae] Tomas McKelvey [Author Vitae] |
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Affiliation: | a Institute for Econometrics, OR and System Theory, Vienna University of Technology, Argentinierstrasse 8, Vienna 1040, Austria b Department of Signals and Systems, Chalmers University of Technology, Göteborg SE-412 96, Sweden |
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Abstract: | In this paper, we study a novel parametrization for state-space systems, namely data driven local coordinates (DDLC) which have recently been introduced and applied. Even though DDLC has meanwhile become the default parametrization used in the system identification toolbox of the software package MATLAB, an analysis of properties of DDLC, which are relevant to identification, has not been performed up to now. In this paper, we provide insights into the geometry and topology of the DDLC construction and show a number of results which are important for actual identification such as maximum likelihood-type estimation. |
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Keywords: | State-space models Parametrization Optimization Linear systems |
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