Abstract
We introduce in this chapter the correlation and covariance matrices of a complex random vector. The Hermitian nature of these matrices allows their diagonalization in the basis of their orthogonal eigenvectors. These concepts are discussed on jointly Gaussian variables. We study the principal component analysis of a vector of observations and the optimum Karhunen-Loève development.
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© 2016 Springer International Publishing Switzerland
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Cohen Tenoudji, F. (2016). Correlation and Covariance Matrices of a Complex Random Vector. In: Analog and Digital Signal Analysis. Modern Acoustics and Signal Processing. Springer, Cham. https://doi.org/10.1007/978-3-319-42382-1_23
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DOI: https://doi.org/10.1007/978-3-319-42382-1_23
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Publisher Name: Springer, Cham
Print ISBN: 978-3-319-42380-7
Online ISBN: 978-3-319-42382-1
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