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Algorithms for Bayesian estimation of spline model structure. (English) Zbl 0781.93090
Summary: A special case of model structure identification is studied. Convolution models with the kernel described by first order spline-functions are tested. A fast algorithm for finding the most probable structure of the model is described.
93E11 Filtering in stochastic control theory
62F15 Bayesian inference
93E12 Identification in stochastic control theory
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[1] M. Kárný: Bayesian estimation of model order. Problems Control Inform. Theory 9 (1980), 1, 33-46. · Zbl 0444.93046
[2] M. Kárný: Algorithms for determining the model structure of a controlled system. Kybernetika 19 (1983), 164-178.
[3] M. Kárný: Quantification of prior knowledge about global characteristic of linear normal model. Kybernetika 20 (1984), 164-178.
[4] M. Kárný I. Nagy J. Böhm, A. Halousková: Design of spline-based self-tuners. Kybernetika 26 (1990), 1, 17-30. · Zbl 0712.93030
[5] V. Peterka: Bayesian approach to system identification. Trends and Progress in System Identi- fication (P. EykhofF, Pergamon Press, Oxford 1981, pp. 239-304. · Zbl 0451.93059
[6] J. Spousta: Structure Estimation of Spline-Description of Dynamic Systems (in Czech). Ph.D. Dissertation, Institute of Information Theory and Automation, Czechoslovak Academy of Sciences, Prague 1990.
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