Filtering Problem for Functionals of Stationary Sequences

  • Mikhail Moklyachuk Kyiv National Taras Shevchenko University
  • Maksym Luz Kyiv National Taras Shevchenko University
DOI: https://doi.org/10.19139/soic.v4i1.172
Keywords: Stationary stochastic sequence, optimal linear mean-square estimate, mean square error, least favorable spectral density, minimax-robust estimate, minimax-robust spectral characteristi

Abstract

In this paper, we consider the problem of the mean-square optimal linear estimation of functionals which depend on the unknown values of a stationary stochastic sequence from observations with noise. In the case of spectral certainty in which the spectral densities of the sequences are exactly known, we propose formulas for calculating the spectral characteristic and value of the mean-square error of the estimate by using the Fourier coefficients of some functions from the spectral densities. When the spectral densities are not exactly known but a class of admissible spectral densities is given, the minimax-robust method of estimation is applied. Formulas for determining the least favourable spectral densities and the minimax-robust spectral characteristics of the optimal estimates of the functionals are proposed for some specific classes of admissible spectral densities.

Author Biographies

Mikhail Moklyachuk, Kyiv National Taras Shevchenko University
Department of Probability Theory, Statistics and Actuarial Mathematics, Professor
Maksym Luz, Kyiv National Taras Shevchenko University
Department of Probability Theory, Statistics and Actuarial Mathematics, PhD Student

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Published
2016-02-28
How to Cite
Moklyachuk, M., & Luz, M. (2016). Filtering Problem for Functionals of Stationary Sequences. Statistics, Optimization & Information Computing, 4(1), 68-83. https://doi.org/10.19139/soic.v4i1.172
Issue
Vol 4 No 1 (2016)
Section
Research Articles
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