The geometric mean of power (amplitude) spectra has a much smaller bias than the classical arithmetic (RMS) averaging

Author

Pintelon, Rik ; Schoukens, J. ; Renneboog, J.

Author_Institution

Nat. Fund for Sci. Res., Vrije Univ., Brussels, Belgium

Volume

37

Issue

2

fYear

1988

fDate

6/1/1988 12:00:00 AM

Firstpage

213

Lastpage

218

Abstract

The statistical properties of the geometric mean of power (amplitude) spectra resulting from a discrete Fourier transform (DFT) are compared with those of arithmetic (RMS) averaging. The statistical properties are verified by means of frequency-domain and time-domain simulations. It is shown that the asymptotic bias of the geometric mean is a function of the fourth-order moments of the measurement noise

Keywords

fast Fourier transforms; frequency-domain analysis; measurement theory; random noise; spectral analysis; statistical analysis; time-domain analysis; RMS; amplitude spectra; arithmetic averaging; asymptotic bias; discrete Fourier transform; fourth-order moments; frequency-domain; geometric mean; measurement noise; power spectra analysis; statistical properties; time-domain simulations; Arithmetic; Coherence; Discrete Fourier transforms; Electric variables measurement; H infinity control; Noise measurement; Pollution measurement; Stochastic resonance; Tin; Transfer functions;

fLanguage

English

Journal_Title

Instrumentation and Measurement, IEEE Transactions on

Publisher

ieee

ISSN

0018-9456

Type

jour

DOI

10.1109/19.6054

Filename

6054