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Effective Signal Extraction Via Local Polynomial Approximation Under Long-Range Dependency Conditions

Authors
  • Artemov, A. V.1, 2
  • 1 Complex Systems Modeling Laboratory, Lomonosov Moscow State University, Lomonosovskii pr. 27-1, Moscow, 119991, Russia , Moscow (Russia)
  • 2 Yandex Data Factory, ul. L’va Tolstogo 16, Moscow, 119021, Russia , Moscow (Russia)
Type
Published Article
Journal
Lobachevskii Journal of Mathematics
Publisher
Pleiades Publishing
Publication Date
Apr 17, 2018
Volume
39
Issue
3
Pages
309–320
Identifiers
DOI: 10.1134/S1995080218030101
Source
Springer Nature
Keywords
License
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Abstract

We study the signal extraction problemwhere a smooth signal is to be estimated against a long-range dependent noise. We consider an approach employing local estimates and derive a theoretically optimal (maximum likelihood) filter for a polynomial signal. On its basis, we propose a practical signal extraction algorithm and adapt it to the extraction of quasi-seasonal signals. We further study the performance of the proposed signal extraction scheme in comparison with conventional methods using the numerical analysis and real-world datasets.

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