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Nonminimax filtering in unknown irregular constrained observation noise. / Granichin, ON.

в: Automation and Remote Control, Том 63, № 9, 09.2002, стр. 1482-1488.

Результаты исследований: Научные публикации в периодических изданияхстатьяРецензирование

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Granichin, ON. / Nonminimax filtering in unknown irregular constrained observation noise. в: Automation and Remote Control. 2002 ; Том 63, № 9. стр. 1482-1488.

BibTeX

@article{6f1d18e8382449f6971f8c51b09bbd66,
title = "Nonminimax filtering in unknown irregular constrained observation noise",
abstract = "A new formulation of prediction of the values of a random process generated by white noise passing through a linear filter was discussed. It was assumed that observations were carried out in an unknown irregular constrained noise and the coefficients of signal transformation in the observation channel were unknown random variables. A randomized variant of the linear predicting filter which, under certain conditions, is superior to the minimax algorithms was proposed.",
author = "ON Granichin",
year = "2002",
month = sep,
doi = "10.1023/A:1020090422744",
language = "Английский",
volume = "63",
pages = "1482--1488",
journal = "Automation and Remote Control",
issn = "0005-1179",
publisher = "МАИК {"}Наука/Интерпериодика{"}",
number = "9",

}

RIS

TY - JOUR

T1 - Nonminimax filtering in unknown irregular constrained observation noise

AU - Granichin, ON

PY - 2002/9

Y1 - 2002/9

N2 - A new formulation of prediction of the values of a random process generated by white noise passing through a linear filter was discussed. It was assumed that observations were carried out in an unknown irregular constrained noise and the coefficients of signal transformation in the observation channel were unknown random variables. A randomized variant of the linear predicting filter which, under certain conditions, is superior to the minimax algorithms was proposed.

AB - A new formulation of prediction of the values of a random process generated by white noise passing through a linear filter was discussed. It was assumed that observations were carried out in an unknown irregular constrained noise and the coefficients of signal transformation in the observation channel were unknown random variables. A randomized variant of the linear predicting filter which, under certain conditions, is superior to the minimax algorithms was proposed.

U2 - 10.1023/A:1020090422744

DO - 10.1023/A:1020090422744

M3 - статья

VL - 63

SP - 1482

EP - 1488

JO - Automation and Remote Control

JF - Automation and Remote Control

SN - 0005-1179

IS - 9

ER -

ID: 5016558