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On Asymptotically Minimax Nonparametric Detection of Signal in Gaussian White Noise. / Ermakov, M. S.

в: Journal of Mathematical Sciences (United States), Том 251, № 1, 01.11.2020, стр. 78-87.

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Harvard

Ermakov, MS 2020, 'On Asymptotically Minimax Nonparametric Detection of Signal in Gaussian White Noise', Journal of Mathematical Sciences (United States), Том. 251, № 1, стр. 78-87. https://doi.org/10.1007/s10958-020-05067-7

APA

Ermakov, M. S. (2020). On Asymptotically Minimax Nonparametric Detection of Signal in Gaussian White Noise. Journal of Mathematical Sciences (United States), 251(1), 78-87. https://doi.org/10.1007/s10958-020-05067-7

Vancouver

Ermakov MS. On Asymptotically Minimax Nonparametric Detection of Signal in Gaussian White Noise. Journal of Mathematical Sciences (United States). 2020 Нояб. 1;251(1):78-87. https://doi.org/10.1007/s10958-020-05067-7

Author

Ermakov, M. S. / On Asymptotically Minimax Nonparametric Detection of Signal in Gaussian White Noise. в: Journal of Mathematical Sciences (United States). 2020 ; Том 251, № 1. стр. 78-87.

BibTeX

@article{0cc9d58e71494a53a2c8da6682107d44,
title = "On Asymptotically Minimax Nonparametric Detection of Signal in Gaussian White Noise",
abstract = "For the problem of nonparametric detection of signal in Gaussian white noise, strong asymptotically minimax tests are found. The sets of alternatives are balls in the Besov space Bs2∞ with “small” balls in L2 removed. The balls in the Besov space are defined in terms of orthogonal expansions of functions in trigonometrical basis. Similar result is also obtained for nonparametric hypothesis testing on a solution of ill-posed linear inverse problem with Gaussian random noise. Bibliography: 19 titles.",
author = "Ermakov, {M. S.}",
note = "Publisher Copyright: {\textcopyright} 2020, Springer Science+Business Media, LLC, part of Springer Nature. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.",
year = "2020",
month = nov,
day = "1",
doi = "10.1007/s10958-020-05067-7",
language = "English",
volume = "251",
pages = "78--87",
journal = "Journal of Mathematical Sciences",
issn = "1072-3374",
publisher = "Springer Nature",
number = "1",

}

RIS

TY - JOUR

T1 - On Asymptotically Minimax Nonparametric Detection of Signal in Gaussian White Noise

AU - Ermakov, M. S.

N1 - Publisher Copyright: © 2020, Springer Science+Business Media, LLC, part of Springer Nature. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020/11/1

Y1 - 2020/11/1

N2 - For the problem of nonparametric detection of signal in Gaussian white noise, strong asymptotically minimax tests are found. The sets of alternatives are balls in the Besov space Bs2∞ with “small” balls in L2 removed. The balls in the Besov space are defined in terms of orthogonal expansions of functions in trigonometrical basis. Similar result is also obtained for nonparametric hypothesis testing on a solution of ill-posed linear inverse problem with Gaussian random noise. Bibliography: 19 titles.

AB - For the problem of nonparametric detection of signal in Gaussian white noise, strong asymptotically minimax tests are found. The sets of alternatives are balls in the Besov space Bs2∞ with “small” balls in L2 removed. The balls in the Besov space are defined in terms of orthogonal expansions of functions in trigonometrical basis. Similar result is also obtained for nonparametric hypothesis testing on a solution of ill-posed linear inverse problem with Gaussian random noise. Bibliography: 19 titles.

UR - http://www.scopus.com/inward/record.url?scp=85092485224&partnerID=8YFLogxK

U2 - 10.1007/s10958-020-05067-7

DO - 10.1007/s10958-020-05067-7

M3 - Article

AN - SCOPUS:85092485224

VL - 251

SP - 78

EP - 87

JO - Journal of Mathematical Sciences

JF - Journal of Mathematical Sciences

SN - 1072-3374

IS - 1

ER -

ID: 71601040