Statistics and Its Interface

Volume 12 (2019)

Number 1

Two asymptotic approaches for the exponential signal and harmonic noise in Singular Spectrum Analysis

Pages: 49 – 59

DOI: http://dx.doi.org/10.4310/SII.2019.v12.n1.a5

Authors

Elizaveta Ivanova (Speech Technology Center, St. Petersburg, Russia)

Vladimir Nekrutkin (St. Petersburg State University, St. Petersburg, Russia)

Abstract

The general theoretical approach to the asymptotic extraction of the signal series from the perturbed signal with the help of Singular Spectrum Analysis (briefly, SSA) was already outlined in Nekrutkin 2010, SII, v. 3, 297–319.

In this paper we consider the example of such an analysis applied to the increasing exponential signal and the sinusoidal noise. It is proved that if the signal rapidly tends to infinity, then the so-called reconstruction errors of SSA do not uniformly tend to zero as the series length tends to infinity. More precisely, in this case any finite number of last terms of the error series does not tend to any finite or infinite values.

On the contrary, for the “discretization” scheme with the exponential signal bounded from above, all elements of the error series tend to zero. This effect shows that the discretization model can be an effective tool in the theoretical SSA considerations with increasing signals.

Keywords

signal subspace methods, singular spectrum analysis, perturbation expansion, asymptotic analysis, signal extraction

2010 Mathematics Subject Classification

Primary 65F30, 65G99. Secondary 65F15.

Full Text (PDF format)

Received 10 January 2018

Published 26 October 2018