English

Filtering Problem for Functionals of Stationary Sequences

Statistics Theory 2024-06-25 v1 Statistics Theory

Abstract

The problem of the mean-square optimal linear estimation of functionals which depend on the unknown values of a stationary stochastic sequence from observations of the sequence with noise is considered. In the case of spectral certainty, where 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, which are determined using the Fourier coefficients of some functions from the spectral densities. The minimax-robust method of estimation is applied in the case of spectral uncertainty, where the spectral densities are not exactly known, but a class of admissible spectral densities is given. Formulas for determining the least favorable 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.

Keywords

Cite

@article{arxiv.2406.15975,
  title  = {Filtering Problem for Functionals of Stationary Sequences},
  author = {Maksym Luz and Mikhail Moklyachuk},
  journal= {arXiv preprint arXiv:2406.15975},
  year   = {2024}
}

Comments

arXiv admin note: text overlap with arXiv:1804.08408, arXiv:1609.01679

R2 v1 2026-06-28T17:16:05.326Z