Bayes Factors for Testing the Equality of Covariance Matrix Eigenvalues

1996 ◽  
pp. 305-314
Author(s):  
Robert E. McCulloch ◽  
Peter E. Rossi
Keyword(s):  
Covariance Matrix ◽  
Bayes Factors ◽  
Matrix Eigenvalues

SPATIAL SELECTION OF WIDE-BAND SOURCES BY COVARIANCE MATRIX EIGENVALUES

2014 ◽  
Vol 73 (9) ◽  
pp. 793-801
Author(s):  
O. V. Sytnik ◽  
V. M. Kartashov ◽  
A.A. Suprun
Keyword(s):  
Covariance Matrix ◽  
Wide Band ◽  
Spatial Selection ◽  
Matrix Eigenvalues ◽  
Selection Of

scholarly journals Classification of Covariance Matrix Eigenvalues in Polarimetric SAR for Environmental Monitoring Applications

2019 ◽  
Vol 34 (6) ◽  
pp. 28-43 ◽  
Author(s):  
Pia Addabbo ◽  
Filippo Biondi ◽  
Carmine Clemente ◽  
Danilo Orlando ◽  
Luca Pallotta
Keyword(s):  
Environmental Monitoring ◽  
Covariance Matrix ◽  
Polarimetric Sar ◽  
Monitoring Applications ◽  
Matrix Eigenvalues

Characterizing the long-period seismicity of Teide volcano in Tenerife (Canary Islands, Spain)

2020 ◽  
Author(s):  
Jean Soubestre ◽  
Luca D'Auria ◽  
José Barrancos ◽  
Germán D. Padilla ◽  
Léonard Seydoux ◽  
...  
Keyword(s):  
Covariance Matrix ◽  
Canary Islands ◽  
Seismic Data ◽  
Monitoring Network ◽  
Eigenvalues And Eigenvectors ◽  
Long Period ◽  
Matrix Eigenvalues ◽  
Teide Volcano ◽  
Eigenvalues Distribution ◽  
Long Period Event

<p>The volcanic long-period seismicity, composed of long-period events and volcanic tremors, constitutes an important attribute of volcanic unrest. Its detection and characterization is therefore a key aspect of volcano monitoring. In the present work, a method based on the seismic network covariance matrix, the equivalent in the frequency domain of the cross-correlation matrix, is used to automatically detect and locate long-period events of the Teide volcano on the island of Tenerife (Canary Islands, Spain). The method is based on the analysis of eigenvalues and eigenvectors of the network covariance matrix.</p><p>Long-period events are detected through the time evolution of the width of the network covariance matrix eigenvalues distribution, which is a proxy of the number of sources acting in the wavefield. Each detected long-period event is then located using the moveout information of the corresponding first eigenvector. Three years of seismic data (from 2017 to 2019) continuously recorded by the Red Sísmica Canaria (C7), a permanent monitoring network composed of 17 broadband stations operated by the Instituto Volcanológico de Canarias (INVOLCAN), are analysed. The obtained locations are compared with potential locations from INVOLCAN’s catalog, obtained by a standard approach based on manual phases picking.</p>

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