TY - GEN
T1 - Efficient characterization of stochastic electromagnetic fields using eigenvalue decomposition and principal component analysis methods
AU - Asenov, Tatjana
AU - Russer, Johannes A.
AU - Russer, Peter
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/10/17
Y1 - 2014/10/17
N2 - Stochastic electromagnetic fields can be described by the correlation function of the field amplitudes in all pairs of space points. We show that the description of stochastic electromagnetic fields by correlation matrices can be simplified using the principal component analysis (PCA) for eigenvalue decomposition. In this paper, the principal component analysis and the eigenvalue decomposition approach are applied for decomposing and reducing the correlation matrix describing the correlations of the sampled field amplitudes. Subsequently conventional eigenvalue decomposition and the PCA approaches are compared.
AB - Stochastic electromagnetic fields can be described by the correlation function of the field amplitudes in all pairs of space points. We show that the description of stochastic electromagnetic fields by correlation matrices can be simplified using the principal component analysis (PCA) for eigenvalue decomposition. In this paper, the principal component analysis and the eigenvalue decomposition approach are applied for decomposing and reducing the correlation matrix describing the correlations of the sampled field amplitudes. Subsequently conventional eigenvalue decomposition and the PCA approaches are compared.
UR - http://www.scopus.com/inward/record.url?scp=84919752820&partnerID=8YFLogxK
U2 - 10.1109/URSIGASS.2014.6929549
DO - 10.1109/URSIGASS.2014.6929549
M3 - Conference contribution
AN - SCOPUS:84919752820
T3 - 2014 31th URSI General Assembly and Scientific Symposium, URSI GASS 2014
BT - 2014 31th URSI General Assembly and Scientific Symposium, URSI GASS 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 31st General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2014
Y2 - 16 August 2014 through 23 August 2014
ER -