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The main goal of the course is to familiarize the students with the common generally valid principles of system identification both analogue and discrete
Last update: Pátková Vlasta (29.05.2018)
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Last update: Mareš Jan (07.06.2018)
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R:Tangirala A.K., Principles of System Identification:Theory and Practice, CRC Press, Boca Raton, 2015, ISBN 978-1-4398-9602-0 A:Ljung L.,Systém Identification. Theory for the User,Prentice Hall PTR,N.J.,1999,0136566952 Last update: Kukal Jaromír (04.09.2018)
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lectures, projects and consultations Last update: Mareš Jan (07.06.2018)
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1. Experimental identification - basic scheme, wide and narrow definition of the branch 2. Structure model selection and process dynamics 3. Integral transforms in process identification I 4. Integral transforms in process identification II 5. Least square method, on-line least square method, Extended least square method 6. Strejc- Broid method 7. Advanced statistical methods in identification I 8. Advanced statistical methods in identification II 9. Stochastic models I 10. Stochastic models II 11. Neural nets in identification I 12. Neural nets in identification II 13. Numerical methods in identification 14. Projects
Last update: Mareš Jan (22.04.2020)
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internal materials Last update: Pátková Vlasta (29.05.2018)
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Students will be able to: • work with common identification methods • work with their implementation • evaluate their efficiency • students will take part in one large complex work (beginning with data measuring up to model formulation) • students will use MATLAB interface for model identification Last update: Pátková Vlasta (29.05.2018)
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none Last update: Mareš Jan (07.06.2018)
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none Last update: Mareš Jan (07.06.2018)
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