TY - JOUR
AU - Mikhail Moklyachuk
AU - Maksym Luz
PY - 2016/02/28
Y2 - 2022/05/28
TI - Filtering Problem for Functionals of Stationary Sequences
JF - Statistics, Optimization & Information Computing
JA - Stat., optim. inf. comput.
VL - 4
IS - 1
SE - Research Articles
DO - 10.19139/soic.v4i1.172
UR - http://www.iapress.org/index.php/soic/article/view/20160306
AB - 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.
ER -