Frequency-Domain Identification of Continuous-Time ARMA Models from Non-Uniformly Sampled Data

This paper treats direct identification of continuous-time autoregressive moving average (CARMA) time-series models. The main result is a method for estimating the continuous-time power spectral de ...

[1]  Rolf Johansson,et al.  Identification of continuous-time models , 1994, IEEE Trans. Signal Process..

[2]  Hugues Garnier,et al.  Numerical illustrations of the relevance of direct continuous-time model identification , 2002 .

[3]  Lennart Ljung,et al.  System identification toolbox for use with MATLAB , 1988 .

[4]  Thomas Kailath,et al.  A further note on backwards Markovian models (Corresp.) , 1979, IEEE Trans. Inf. Theory.

[5]  Torsten Söderström,et al.  CONTINUOUS-TIME AR PARAMETER ESTIMATION BY USING PROPERTIES OF SAMPLED SYSTEMS , 2002 .

[6]  S. Weller,et al.  Sampling zeros and the Euler-Frobenius polynomials , 1997, Proceedings of the 36th IEEE Conference on Decision and Control.

[7]  Ali H. Sayed,et al.  Linear Estimation (Information and System Sciences Series) , 2000 .

[8]  Lennart Ljung,et al.  Initialisation aspects for subspace and output-error identification methods , 2003, 2003 European Control Conference (ECC).

[9]  Yves Rolain,et al.  Box-Jenkins continuous-time modeling , 2000, Autom..

[10]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .

[11]  Lennart Ljung,et al.  Frequency-Domain Identification of Continuous-Time Output Error Models from Sampled Data , 2005 .

[12]  Jonas Gillberg,et al.  Methods for Frequency Domain Estimation of Continuous-Time Models , 2004 .

[13]  Erik Larsson.  Identification of Stochastic Continuous-time Systems : Algorithms, Irregular Sampling and Cramér-Rao Bounds , 2003 .

[14]  Torsten Söderström.  Computing stochastic continuous-time models from ARMA models , 1991 .

[15]  Magnus Mossberg,et al.  On possibilities for estimating continuous-time ARMA parameters , 2003 .

[16]  David R. Brillinger,et al.  Time Series , 2018, Randomization, Bootstrap and Monte Carlo Methods in Biology.