Title
Coherence estimate between a random and a periodic signal: Bias, variance, analytical critical values, and normalizing transforms
Abstract
The present work deals with recent results on the sampling distribution of the magnitude-squared coherence (also called just coherence) estimate between a random (Gaussian) and a periodic signal, in order to obtain analytical critical values, alternative expressions for the probability density function (PDF) as well as the variance and bias of the estimate. A comparison with the more general case of coherence estimation when both signals are Gaussian was also provided. The results indicate that the smaller the true coherence (TC) values the closer both distributions become. The behaviour of variance and bias as a function of the number of data segments and the TC is similar for both coherence estimates. Additionally, the effect of a normalizing function (Fisher's z transform) in the coherence estimated between a random and a periodic signal was also evaluated and normality has been nearly achieved. However, the variance was less equalized in comparison with coherence estimate between two Gaussian signals.
Year
DOI
Venue
2009
10.1016/j.jfranklin.2009.07.009
Journal of the Franklin Institute
Keywords
Field
DocType
Coherence,Estimation,Statistics,Periodic input,Fisher's z transform
Sampling distribution,Coherence (statistics),Statistical physics,Periodic function,Coherence (signal processing),Control theory,Coherence (physics),Gaussian,Fisher information,Statistics,Probability density function,Mathematics
Journal
Volume
Issue
ISSN
346
9
0016-0032
Citations 
PageRank 
References 
5
0.59
4
Authors
5