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Modelling and parameter estimation of dynamic systems
Parameter estimation is the process of using observations from a system to develop mathematical models that adequately represent the system dynamics. The assumed model consists of a finite set of parameters, the values of which are calculated using estimation techniques. Most of the techniques that...
Autores principales: | , , |
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Lenguaje: | eng |
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The Institution of Engineering and Technology
2004
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Acceso en línea: | http://cds.cern.ch/record/2066446 |
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author | Raol, JR Girija, G Singh, J |
author_facet | Raol, JR Girija, G Singh, J |
author_sort | Raol, JR |
collection | CERN |
description | Parameter estimation is the process of using observations from a system to develop mathematical models that adequately represent the system dynamics. The assumed model consists of a finite set of parameters, the values of which are calculated using estimation techniques. Most of the techniques that exist are based on least-square minimization of error between the model response and actual system response. However, with the proliferation of high speed digital computers, elegant and innovative techniques like filter error method, H-infinity and Artificial Neural Networks are finding more and mor |
id | cern-2066446 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2004 |
publisher | The Institution of Engineering and Technology |
record_format | invenio |
spelling | cern-20664462021-04-21T20:02:56Zhttp://cds.cern.ch/record/2066446engRaol, JRGirija, GSingh, JModelling and parameter estimation of dynamic systemsMathematical Physics and MathematicsParameter estimation is the process of using observations from a system to develop mathematical models that adequately represent the system dynamics. The assumed model consists of a finite set of parameters, the values of which are calculated using estimation techniques. Most of the techniques that exist are based on least-square minimization of error between the model response and actual system response. However, with the proliferation of high speed digital computers, elegant and innovative techniques like filter error method, H-infinity and Artificial Neural Networks are finding more and morThe Institution of Engineering and Technologyoai:cds.cern.ch:20664462004 |
spellingShingle | Mathematical Physics and Mathematics Raol, JR Girija, G Singh, J Modelling and parameter estimation of dynamic systems |
title | Modelling and parameter estimation of dynamic systems |
title_full | Modelling and parameter estimation of dynamic systems |
title_fullStr | Modelling and parameter estimation of dynamic systems |
title_full_unstemmed | Modelling and parameter estimation of dynamic systems |
title_short | Modelling and parameter estimation of dynamic systems |
title_sort | modelling and parameter estimation of dynamic systems |
topic | Mathematical Physics and Mathematics |
url | http://cds.cern.ch/record/2066446 |
work_keys_str_mv | AT raoljr modellingandparameterestimationofdynamicsystems AT girijag modellingandparameterestimationofdynamicsystems AT singhj modellingandparameterestimationofdynamicsystems |