Square root of a squared block matrix

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SUMMARY

The discussion focuses on computing the square root of a squared block matrix represented as M = [A B; C D], where A, B, C, and D are square matrices. The user, GoodSpirit, seeks assistance in transforming M into a simpler form, specifically M = [P 0; 0 Q], and mentions that M is a covariance matrix, symmetric and semi-positive definite. The conversation highlights the challenges of using eigendecomposition, M = Q Λ Q^T, to derive a solution, indicating that the process leads to complex results.

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GoodSpirit
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Hi everybody,

I’m trying to compute the square root of the following squared block matrix:

<br /> \begin{equation}<br /> M=\begin{bmatrix}<br /> A &amp;B\\<br /> C &amp;D\\<br /> \end{bmatrix}<br /> \end{equation}<br />

(that is M^(1/2))as function of A,B,C, D which are all square matrices.

Can you help me?

I sincerely thank you! :)

All the best

GoodSpirit
 
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Hi GoodSpirit! :smile:

Have you tried transforming it into the form
<br /> \begin{equation}<br /> M=\begin{bmatrix}<br /> P &amp;0\\<br /> 0 &amp;Q\\<br /> \end{bmatrix}<br /> \end{equation}<br />
 
Hi tiny-tim,

Thank you for answering.
That´s an interesting idea but how do you do that...?
It is not easy...
I must say that there is more...
M is a typical covariance matrix so it is symmetric and semi-positive definite.

A and D are symmetric and positive semi-definite (covariance matrices too) and B=C^T and B is the cross covariance matrix of A and D.

My attempt is based on eigendecomposition
$$ M=Q \Lambda Q^T $$
and
$$
M=\begin{bmatrix}
a & b \\
c & d \\
\end{bmatrix}
\begin{bmatrix}
a & b \\
c & d \\
\end{bmatrix}
$$

But it lead to something very complicated.

I really thank you all for your answer!:)

All the best

GoodSpirit
 

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