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Score Evaluation Within the Extended Square-Root Information Filter

  • Maria V. Kulikova
  • Innokenti V. Semoushin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3991)

Abstract

A newly developed algorithm for evaluating the Log Likelihood Gradient (score) of linear discrete-time dynamic systems is presented, based on the extended Square-Root Information Filter (eSRIF). The new result can be used for efficient calculations in gradient-search algorithms for maximum likelihood estimation of the unknown system parameters. The theoretical results are given with the examples showing the superior perfomance of this computational approach over the conventional one.

Keywords

Very Large Scale Integration Linear Dynamic System Linear State Space Model Unknown System Parameter Numerical Score Evaluation 
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

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Maria V. Kulikova
    • 1
  • Innokenti V. Semoushin
    • 2
  1. 1.School of Computational and Applied MathematicsUniversity of the WitwatersrandJohannesburgSouth Africa
  2. 2.Ulyanovsk State UniversityUlyanovskRussia

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