“A method for the identification of state space models from input and output measurements”

Authors: David Di Ruscio,
Affiliation: Telemark University College
Reference: 1995, Vol 16, No 3, pp. 129-143.

Keywords: System identification, combined deterministic and stochastic systems, minimal realization, modeling, state-space methods, time series analysis

Abstract: In this paper we present a simple and general algorithm for the combined deterministic stochastic realization problem directly from known input and output time series. The solution to the pure deterministic as well as the pure stochastic realization problem are special cases of the method presented.

PDF PDF (1704 Kb)        DOI: 10.4173/mic.1995.3.2

DOI forward links to this article:
[1] Jan-Willem van Wingerden, Marco Lovera, Marco Bergamasco, Michel Verhaegen and Gijs van der Veen (2013), doi:10.1049/iet-cta.2012.0653
[2] D.D. Di Ruscio (1997), doi:10.1109/CDC.1997.652337
[3] Daniel N. Miller and Raymond A. de Callafon (2011), doi:10.3182/20110828-6-IT-1002.02597
[4] A.J. Vladova, J.R. Vladov, V. Kushnarenko and N.N. Bakhtadze (2012), doi:10.3182/20120523-3-RO-2023.00278
[5] David Di Ruscio (1997), doi:10.1007/978-1-4612-2252-1_8
[6] Christer Dalen and David Di Ruscio (2022), doi:10.4173/mic.2022.4.1
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  title={{A method for the identification of state space models from input and output measurements}},
  author={Di Ruscio, David},
  journal={Modeling, Identification and Control},
  publisher={Norwegian Society of Automatic Control}