NONPARAMETRIC SIGNAL ESTIMATION WHEN THERE IS INCOMPLETE INFORMATION ON THE NOISE DISTRIBUTION.

A. B. Tsybakov

NONPARAMETRIC SIGNAL ESTIMATION WHEN THERE IS INCOMPLETE INFORMATION ON THE NOISE DISTRIBUTION.

A. B. Tsybakov

Research output: Contribution to journal › Article › peer-review

Abstract

A class of nonparametric signal estimates is proposed on the basis of observations in noise with probability characteristics that are not precisely known. The consistency conditions for these estimates are given, and their rate of convergence is determined. The problem of choosing estimates that are optimal in the sense of rate of convergence is solved.

Original language	English
Pages (from-to)	116-130
Number of pages	15
Journal	Problems of Information Transmission
Volume	82
Issue number	2
Publication status	Published - 1 Jan 1982

Cite this

@article{ffb6305cf4304c49b345cdcda2331db1,

title = "NONPARAMETRIC SIGNAL ESTIMATION WHEN THERE IS INCOMPLETE INFORMATION ON THE NOISE DISTRIBUTION.",

abstract = "A class of nonparametric signal estimates is proposed on the basis of observations in noise with probability characteristics that are not precisely known. The consistency conditions for these estimates are given, and their rate of convergence is determined. The problem of choosing estimates that are optimal in the sense of rate of convergence is solved.",

author = "Tsybakov, \{A. B.\}",

year = "1982",

month = jan,

day = "1",

language = "English",

volume = "82",

pages = "116--130",

journal = "Problems of Information Transmission",

issn = "0032-9460",

number = "2",

}

TY - JOUR

T1 - NONPARAMETRIC SIGNAL ESTIMATION WHEN THERE IS INCOMPLETE INFORMATION ON THE NOISE DISTRIBUTION.

AU - Tsybakov, A. B.

PY - 1982/1/1

Y1 - 1982/1/1

N2 - A class of nonparametric signal estimates is proposed on the basis of observations in noise with probability characteristics that are not precisely known. The consistency conditions for these estimates are given, and their rate of convergence is determined. The problem of choosing estimates that are optimal in the sense of rate of convergence is solved.

AB - A class of nonparametric signal estimates is proposed on the basis of observations in noise with probability characteristics that are not precisely known. The consistency conditions for these estimates are given, and their rate of convergence is determined. The problem of choosing estimates that are optimal in the sense of rate of convergence is solved.

UR - https://www.scopus.com/pages/publications/0020112256

M3 - Article

AN - SCOPUS:0020112256

SN - 0032-9460

VL - 82

SP - 116

EP - 130

JO - Problems of Information Transmission

JF - Problems of Information Transmission

IS - 2

ER -

NONPARAMETRIC SIGNAL ESTIMATION WHEN THERE IS INCOMPLETE INFORMATION ON THE NOISE DISTRIBUTION.

Abstract

Other files and links

Fingerprint

Cite this