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Avtomat. i Telemekh., 2012, Issue 6, Pages 34–51 (Mi at3812)  

This article is cited in 8 scientific papers (total in 8 papers)

Stochastic Systems, Queuing Systems

On efficient parametric identification methods for linear discrete stochastic systems

Yu. V. Tsyganovaa, M. V. Kulikovab

a Ul'yanovsk State University, Ul'yanovsk, Russia
b Lisbon Technical University, Lisbon, Portugal

Abstract: We construct a numerically stable algorithm (with respect to machine rounding errors) of adaptive Kalman filtering in order to solve the parametric identification problem for linear stationary stochastic discrete systems. We solve the problem in the state space. The proposed algorithm is formulated in terms of an orthogonal square-root covariance filter which lets us avoid a standard implementation of the Kalman filter.

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English version:
Automation and Remote Control, 2012, 73:6, 962–975

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Presented by the member of Editorial Board: А. В. Назин

Received: 11.04.2011

Citation: Yu. V. Tsyganova, M. V. Kulikova, “On efficient parametric identification methods for linear discrete stochastic systems”, Avtomat. i Telemekh., 2012, no. 6, 34–51; Autom. Remote Control, 73:6 (2012), 962–975

Citation in format AMSBIB
\Bibitem{TsyKul12}
\by Yu.~V.~Tsyganova, M.~V.~Kulikova
\paper On efficient parametric identification methods for linear discrete stochastic systems
\jour Avtomat. i Telemekh.
\yr 2012
\issue 6
\pages 34--51
\mathnet{http://mi.mathnet.ru/at3812}
\transl
\jour Autom. Remote Control
\yr 2012
\vol 73
\issue 6
\pages 962--975
\crossref{https://doi.org/10.1134/S0005117912060033}
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\scopus{http://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-84864565954}


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    Citing articles on Google Scholar: Russian citations, English citations
    Related articles on Google Scholar: Russian articles, English articles

    This publication is cited in the following articles:
    1. M. V. Kulikova, Yu. V. Tsyganova, “A general approach to constructing parameter identification algorithms in the class of square root filters with orthogonal and $J$-orthogonal tranformations”, Autom. Remote Control, 75:8 (2014), 1402–1419  mathnet  crossref  isi
    2. M. V. Kulikova, J. V. Tsyganova, “Differentiating matrix orthogonal transformations”, Comput. Math. Math. Phys., 55:9 (2015), 1419–1431  mathnet  crossref  crossref  mathscinet  isi  elib  elib
    3. Kulikova M.V., Tsyganova J.V., “Constructing Numerically Stable Kalman Filter-Based Algorithms For Gradient-Based Adaptive Filtering”, Int. J. Adapt. Control Signal Process., 29:11 (2015), 1411–1426  crossref  mathscinet  zmath  isi  elib  scopus
    4. Kulikova M.V., Tsyganova J.V., “A Unified Square-Root Approach For the Score and Fisher Information Matrix Computation in Linear Dynamic Systems”, Math. Comput. Simul., 119 (2016), 128–141  crossref  mathscinet  isi  elib  scopus
    5. Semushin I., Tsyganova J., Kulikova M., Tsyganov A., Peskov A., “Identification of Human Body Daily Temperature Dynamics Via Minimum State Prediction Error Method”, 2016 European Control Conference (Ecc), IEEE, 2016, 2429–2434  crossref  isi
    6. Kulikova M.V., Tsyganova J.V., Semushin I., “Adaptive Wave Filtering For Marine Vessels Within Ud-Based Algorithms”, 2016 European Control Conference (Ecc), IEEE, 2016, 807–812  crossref  isi
    7. Raillon L., Ghiaus C., “An Efficient Bayesian Experimental Calibration of Dynamic Thermal Models”, Energy, 152 (2018), 818–833  crossref  isi  scopus
    8. Yu. V. Tsyganova, A. V. Tsyganov, “O vychislenii znachenii proizvodnykh v LD-razlozhenii parametrizovannykh matrits”, Izvestiya Irkutskogo gosudarstvennogo universiteta. Seriya Matematika, 23 (2018), 64–79  mathnet  crossref
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