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Advances in Electrical and Electronic Engineering
Article . 2019 . Peer-reviewed
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Article . 2019
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Adaptive Robust Efficient Methods for Periodic Signal Processing Observed with Colours Noises

Authors: Pchelintsev, Evgeny; Marcokova, Mariana; Pergamenchtchikov, Serguei;

Adaptive Robust Efficient Methods for Periodic Signal Processing Observed with Colours Noises

Abstract

In this paper, we consider the problem of robust adaptive efficient estimating a periodic signal observed in the transmission channel with the dependent noise defined by non-Gaussian Ornstein-Uhlenbeck processes with unknown correlation properties. Adaptive model selection procedures, based on the shrinkage weighted least squares estimates, are proposed. The comparison between shrinkage and least squares methods is studied and the advantages of the shrinkage methods are analyzed. Estimation properties for proposed statistical algorithms are studied on the basis of the robust mean square accuracy defined as the maximum mean square estimation error over all possible values of unknown noise parameters. Sharp oracle inequalities for the robust risks have been obtained. The robust efficiency of the model selection procedure has been established.

Countries
France, Russian Federation
Keywords

model selection, ornstein-uhlenbeck process, periodic signals, робастный квадратический риск, weighted least squares estimates, sharp oracle inequality, non- parametric regression, выбор модели, non-parametric regression, асимптотическая эффективность, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, непараметрическая регрессия, Asymptotic efficiency, robust quadratic risk, asymptotic efficiency, взвешенные оценки наименьших квадратов, shrinkage estimation, оракульное неравенство, weighted least squares estimates., Орнштейна-Уленбека процесс, TK1-9971, периодические сигналы, Electrical engineering. Electronics. Nuclear engineering, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Ornstein-Uhlenbeck pro- cess

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
Green
Published in a Diamond OA journal