The covariance-variance matrix of a set of observations, Exx, is a symmetric matrix. The covariance matrix of functions of these observations should also be symmetric as the two covariance matrices are related by the equation Eyy= JEXXJT. Using laws on matrix transposition, prove that, indeed, Eyy is symmetric by showing that the product JEXXJT is symmetric, i.e., the original product and its transpose are equal. You need to list the transposition law concerned, or a property of a matrix, at every step of the proof.

MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
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The covariance-variance matrix of a set of
observations, xx, is a symmetric matrix. The
Covariance matrix of functions of these
observations should also be symmetric as the
two covariance matrices are related by the
equation Eyy= JEXXJT. Using laws on matrix
transposition, prove that, indeed, Eyy is
symmetric by showing that the product JEXXJT
is symmetric, i.e., the original product and its
transpose are equal. You need to list the
transposition law concerned, or a property of a
matrix, at every step of the proof.
Transcribed Image Text:The covariance-variance matrix of a set of observations, xx, is a symmetric matrix. The Covariance matrix of functions of these observations should also be symmetric as the two covariance matrices are related by the equation Eyy= JEXXJT. Using laws on matrix transposition, prove that, indeed, Eyy is symmetric by showing that the product JEXXJT is symmetric, i.e., the original product and its transpose are equal. You need to list the transposition law concerned, or a property of a matrix, at every step of the proof.
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