Effective Signal Extraction Via Local Polynomial Approximation Under Long-Range Dependency Conditions
- Authors: Artemov A.V.1,2
-
Affiliations:
- Lomonosov Moscow State University
- Yandex Data Factory
- Issue: Vol 39, No 3 (2018)
- Pages: 309-320
- Section: Article
- URL: https://journals.rcsi.science/1995-0802/article/view/201781
- DOI: https://doi.org/10.1134/S1995080218030101
- ID: 201781
Cite item
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.
About the authors
A. V. Artemov
Lomonosov Moscow State University; Yandex Data Factory
Author for correspondence.
Email: artemov@physics.msu.ru
Russian Federation, Lomonosovskii pr. 27-1, Moscow, 119991; ul. L’va Tolstogo 16, Moscow, 119021