Box-Jenkins alike identification using nonparametric noise models
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Publication:705191
DOI10.1016/j.automatica.2004.06.016zbMath1077.93052OpenAlexW2090118980MaRDI QIDQ705191
Yves Rolain, Rik Pintelon, Johan Schoukens
Publication date: 26 January 2005
Published in: Automatica (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.automatica.2004.06.016
Related Items (5)
Box-Jenkins identification revisited. II: Applications ⋮ Recursive least squares identification of hybrid Box-Jenkins model structure in open-loop and closed-loop ⋮ Validity of the standard cross-correlation test for model structure validation ⋮ Estimating models with high-order noise dynamics using semi-parametric weighted null-space fitting ⋮ On the equivalence of time and frequency domain maximum likelihood estimation
Cites Work
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- On covariance function tests used in system identification
- Study of conditional ML estimators in time and frequency-domain system identification
- Frequency-domain system identification using non-parametric noise models estimated from a small number of data sets
- Frequency domain system identification using arbitrary signals
- Frequency domain system identification with missing data
- Adaptive smoothing methods for frequency-function estimation
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