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

A. V. Artemov

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

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.

Original languageEnglish
Pages (from-to)309-320
Number of pages12
JournalLobachevskii Journal of Mathematics
Volume39
Issue number3
DOIs
Publication statusPublished - 1 Apr 2018
Externally publishedYes

Keywords

  • fractional Brownian motion
  • local polynomial estimate
  • long-range dependence
  • signal extraction
  • Smooth trend

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