Open AccessComparative analysis of power spectrum estimation methods
Author(s) -
Gintarė Petreikytė,
Kazys Kazlauskas
Publication year - 2010
Publication title -
lietuvos matematikos rinkinys
Language(s) - English
Resource type - Journals
eISSN - 2335-898X
pISSN - 0132-2818
DOI - 10.15388/lmr.2010.55
Subject(s) - spectral density , nonparametric statistics , parametric statistics , subspace topology , spectrum (functional analysis) , estimation , mathematics , noise (video) , statistics , power (physics) , noise power , cross spectrum , algorithm , computer science , frequency domain , artificial intelligence , physics , mathematical analysis , engineering , systems engineering , quantum mechanics , image (mathematics)
The subject of this paper is the comparative analysis of the eleven most important nonparametric, parametric and subspace power spectrum estimation methods. Theoretically and experimentally we analyse how the frequency resolution of the spectrum estimation methods depends on the signal length, signal-to-noise ratio (SNR) and the order parametric methods.