Automation and Remote Control

, Volume 73, Issue 6, pp 962–975 | Cite as

On efficient parametric identification methods for linear discrete stochastic systems

  • Yu. V. Tsyganova
  • M. V. Kulikova
Stochastic Systems, Queueing Systems


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.


Remote Control Cholesky Decomposition Sensitivity Equation Standard Implementation Newton Type Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Pleiades Publishing, Ltd. 2012

Authors and Affiliations

  • Yu. V. Tsyganova
    • 1
  • M. V. Kulikova
    • 2
  1. 1.Ul’yanovsk State UniversityUl’yanovskRussia
  2. 2.Lisbon Technical UniversityLisbonPortugal

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