Institute of Information Theory and Automation

You are here

Bibliography

Conference Paper (international conference)

Partial Forgetting in Autoregression Models

Dedecius Kamil

: Proceedings of the 9th International PhD Workshop on Systems and Control, Young Generation Viewpoint, p. 1-6 , Eds: Gašperin Matej, Pregelj Boštjan

: 9th International PhD Workshop on Systems and Control: A Young Generation Viewpoint, (Izola, SI, 01.10.2008-03.10.2008)

: CEZ:AV0Z10750506

: autoregression model, forgetting, partial forgetting, estimation

: http://library.utia.cas.cz/separaty/2008/AS/dedecius-partial%20forgetting%20in%20autoregression%20models.pdf

(eng): The assumption of constant parameters of the autoregression model sometimes fails, as the parameters may vary in time. If the parameters vary slowly, the problem is often solved using various forgetting methods like exponential forgetting, linear forgetting etc. However, most of them work on the model parameters probability density function with one common forgetting rate. In the case of different variability of individual parameters, these methods might fail. The developed partial forgetting method gives a new approach, which solves this problem. It releases individual parameters and allows them to change with different rates.

(cze): Parciální zapomínání v autoregresních modelech

: BC

2019-01-07 08:39