Parameter Estimation With Partial Forgetting Method

0328717 - ÚTIA 2010 RIV FR eng C - Conference Paper (international conference)
Dedecius, Kamil - Nagy, Ivan - Kárný, Miroslav - Pavelková, Lenka
Parameter Estimation With Partial Forgetting Method.
[Odhad parametrů metodou parcialního zapomínání.]
Proceedings of the 15th IFAC Symposium on Identification and System Parameter Estimation - SYSID 2009. Saint-Malo: IFAC, 2009, s. 534-539.
[15th IFAC Symposium on Identification and System Parameter Estimation - SYSID 2009. Saint-Malo (FR), 06.07.2009-08.07.2009]
R&D Projects: GA MŠMT 2C06001; GA ČR GA102/08/0567
Institutional research plan: CEZ:AV0Z10750506
Keywords : autoregressive models * model * parameter estimation * prediction * regression
Subject RIV: BD - Theory of Information
http://library.utia.cas.cz/separaty/2009/AS/dedecius-parameter estimation with partial forgetting method.pdf

The paper proposes a new estimating algorithm for linear parameter varying systems with slowly time-varying parameters when the rate of change of individual parameters is different. It introduces a true probability density function, describing ideally the behaviour of parameters. However, as it is unknown, we search for its best approximation. A convex combination of point estimates, defined by individual hypotheses about the true probability density function, is then approximated by a single density. That serves as the best available description of parameters' behaviour and it is therefore suitable e.g. for prediction purposes.

Článek představuje nový rozhodovací algoritmus pro lineární parametry různých systémů s pomalými časově-variačními parametry, kde je velmi malá pravděpodobnost, že se jednotlivé parametry změní.
Permanent Link: http://hdl.handle.net/11104/0174962