How to solve for matrix V ? A = V*S*V'

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In summary, to solve for matrix V in the equation A = V*S*V', where A, V, and S are all square and invertible matrices, one can use the eigenvalue decomposition method. A and S must be symmetric and have the same eigenvalues for this method to work. V can be found by taking the square root of the eigenvalues of A and inverting the eigenvalues of S. V is an orthogonal matrix with its columns being the eigenvectors of A. This can be easily calculated using software packages such as MATLAB.
  • #1
cr2504life
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How to solve for matrix V ?? A = V*S*V'

I have A, V, and S (all matricies, square and invertable).
A = V*S*V'

where V' is transpose(V)

I know A and S, how do I solve for V ??

S is symmetric incase that helps.

Much appreciated.

J.
 
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  • #2


Is A also symmetric? If so, this can be reduced to an eigenvalue problem.

Wait -- duh. Of course A is symmetric, or there would be no solution. So, here's what you do. Diagonalize both A and S:

A = P L P'
S = Q L Q'

L is the diagonal matrix of eigenvalues. The two matrices must have the same eigenvalues, or there is no solution. P and Q are the respective eigenvector matrics, and they are orthogonal. (I assume we're dealing with real matrices.) Now

L = P' A P = Q' S Q
A = P Q' S Q P'
V = P Q'
 
  • #3


I made a mistake. The eigenvalues of the two matrices need not be the same. (For some reason I was thinking you needed a similarity transformation.) Suppose the eigenvalue decomposition of S is Q M Q' (Q orthogonal, M diagonal). Then:

[tex]
\begin{eqnarray*}
S & = & Q M^{1/2} L^{-1/2} L L^{-1/2} M^{1/2} Q^T \\
L & = & L^{1/2} M^{-1/2} Q^T S Q M^{-1/2} L^{1/2} \\
& = & P^T A P \\
A & = & P L^{1/2} M^{-1/2} Q^T S Q M^{-1/2} L^{1/2} P^T\\
V & = & P L^{1/2} M^{-1/2} Q^T \\
\end{eqnarray*}
[/tex]

[itex]L^{1/2} M^{-1/2}[/itex] will have imaginary values if any eigenvalues of S are opposite in sign to those of A.
 
  • #4


Thanks pmsrw3, I am going to give that a try, I'll post my finings.

and yes, A is symmetric too. Also, S is a diagonal matrix containing the eigenvalues of A.
 
  • #5


cr2504life said:
and yes, A is symmetric too. Also, S is a diagonal matrix containing the eigenvalues of A.
Ah! You should have mentioned that. You just want to diagonalize a symmetric matrix. This is a standard problem. There are tons of software packages that will do it.
 
  • #6


So, since S is a diagonal matrix containing the eigenvalues of A, V seems to be a matrix whos corresponding columns are the eigen vectors of A.

A = V*S*V' checks out.

I should have mentioned that S was a diagonal matrix which containes the eigenvalues of A. Ppmsrw3 thanks for your general solution to this problem, I wouldn't have solved this without your help.
 
  • #7


cr2504life said:
So, since S is a diagonal matrix containing the eigenvalues of A, V seems to be a matrix whos corresponding columns are the eigen vectors of A.

A = V*S*V' checks out.

I should have mentioned that S was a diagonal matrix which containes the eigenvalues of A. Ppmsrw3 thanks for your general solution to this problem, I wouldn't have solved this without your help.
That's right: each column of V is an eigenvector of A, and V is an orthogonal matrix (V V' = V' V = I). (Or, I should say, it can always be chosen to be orthogonal.)
 
  • #8


pmsrw3 said:
That's right: each column of V is an eigenvector of A, and V is an orthogonal matrix (V V' = V' V = I). (Or, I should say, it can always be chosen to be orthogonal.)

Im trying this out in MATLAB, VV' = V'V = I, yup, confirmed in MATLAB.

and to find V, [V,S] = eig(A);

I really only know this eigenvalue/vector stuff on a superficial level.

Thanks.
 

1. How do I solve for matrix V in the equation A = V*S*V'?

To solve for matrix V in this equation, you can use a process called matrix decomposition or factorization. One commonly used method is the eigenvalue decomposition, where V is equal to the matrix of eigenvectors of A. Other methods include the singular value decomposition and the Cholesky decomposition.

2. What is the purpose of solving for matrix V in this equation?

The equation A = V*S*V' is commonly used in linear algebra to represent the diagonalization of a symmetric matrix. Solving for matrix V allows us to find the eigenvectors of A, which can help us understand the behavior and properties of the original matrix.

3. Can I solve for matrix V if A is not a symmetric matrix?

No, in order to solve for matrix V using the methods mentioned above, A must be a symmetric matrix. If A is not symmetric, other methods such as the Jordan decomposition or the QR decomposition can be used to find the necessary matrices.

4. Is there a unique solution for matrix V in this equation?

Yes, for a given symmetric matrix A, there is a unique solution for matrix V. This is because the eigenvectors of A are orthogonal to each other and form a basis for the vector space of A. Therefore, there is only one set of eigenvectors that can diagonalize A.

5. Are there any software tools or programs that can help me solve for matrix V?

Yes, there are many software tools and programs that can help you solve for matrix V in this equation, such as MATLAB, Mathematica, and Python libraries like NumPy and SciPy. These programs have built-in functions for performing various matrix decompositions and can provide the solution for matrix V quickly and accurately.

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