Coherence estimate between a random and a periodic signal: Bias, variance, analytical critical values, and normalizing transforms

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 funct...

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Published in:Journal of the Franklin Institute Vol. 346; no. 9; pp. 841 - 853
Main Authors: Miranda de Sá, Antonio Mauricio F.L., Ferreira, Danton D., Dias, Edson W., Mendes, Eduardo M.A.M., Felix, Leonardo B.
Format: Journal Article
Language:English
Published: Kidlington Elsevier Ltd 01-11-2009
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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.
AbstractList 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.
Author Ferreira, Danton D.
Dias, Edson W.
Felix, Leonardo B.
Mendes, Eduardo M.A.M.
Miranda de Sá, Antonio Mauricio F.L.
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  givenname: Antonio Mauricio F.L.
  surname: Miranda de Sá
  fullname: Miranda de Sá, Antonio Mauricio F.L.
  email: amflms@peb.ufrj.br
  organization: Biomedical Engineering Program/COPPE, Federal University of Rio de Janeiro, P.O. Box 68510, CEP 21941-972 Rio de Janeiro, RJ, Brazil
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  givenname: Danton D.
  surname: Ferreira
  fullname: Ferreira, Danton D.
  organization: Electrical Engineering Graduation Program, Federal University of Juiz de Fora, CEP 36036-900 Juiz de Fora, MG, Brazil
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  givenname: Edson W.
  surname: Dias
  fullname: Dias, Edson W.
  organization: Federal University of São João del Rei – Alto Paraopeba Campus, CEP: 36420-000, Ouro Branco, MG, Brazil
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  givenname: Eduardo M.A.M.
  surname: Mendes
  fullname: Mendes, Eduardo M.A.M.
  organization: Electrical Engineering Graduation Program, Federal University of Minas Gerais, CEP 31270-901 Belo Horizonte, MG, Brazil
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  givenname: Leonardo B.
  surname: Felix
  fullname: Felix, Leonardo B.
  organization: Department of Electrical and Production Engineering, Federal University of Viçosa, CEP 36570-000 Viçosa, MG, Brazil
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Issue 9
Keywords Periodic input
Fisher's z transform
Statistics
Estimation
Coherence
Correlation coefficient
Random signal
Statistical analysis
Critical value
Probabilistic approach
Bias
Signal estimation
Periodic signal
Variance
Sampling distribution
Fisher information
Z transformation
Gaussian signal
Probability density function
Language English
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Snippet The present work deals with recent results on the sampling distribution of the magnitude-squared coherence (also called just coherence) estimate between a...
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SubjectTerms Applied sciences
Coherence
Detection, estimation, filtering, equalization, prediction
Estimation
Exact sciences and technology
Fisher's z transform
Information, signal and communications theory
Periodic input
Signal and communications theory
Signal, noise
Statistics
Telecommunications and information theory
Title Coherence estimate between a random and a periodic signal: Bias, variance, analytical critical values, and normalizing transforms
URI https://dx.doi.org/10.1016/j.jfranklin.2009.07.009
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