Permutation matrix and PA = LDU

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Homework Help Overview

The discussion revolves around finding the PA = LDU factorizations for a given matrix A and the implications of choosing different permutation matrices P during the factorization process.

Discussion Character

  • Exploratory, Assumption checking, Problem interpretation

Approaches and Questions Raised

  • Participants explore the effect of different permutation matrices on the LU factorization of the same matrix A, questioning whether different choices of P should yield the same results.

Discussion Status

Some participants have provided insights into the nature of LU decomposition with pivoting and the role of permutation matrices, noting that different permutations lead to different factorizations. The discussion is ongoing with participants clarifying their understanding of the process.

Contextual Notes

There is a mention of the potential confusion surrounding the choice of permutation matrix P, as it is typically determined by the LU decomposition algorithm rather than chosen arbitrarily. The implications of performing LU decomposition without pivoting are also under consideration.

Dafe
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Homework Statement


Find the PA = LDU factorizations for:



A = [tex]\left[ \begin{array}{ccc} 0 & 1 & 1 \\ 1 & 0 & 1 \\ 2 & 3 & 4 \end{array} \right][/tex]

The author chooses a permutation matrix :

P = [tex]\left[ \begin{array}{ccc} 0 & 1 & 0 \\ 1 & 0 & 0 \\ 0 & 0 & 1 \end{array} \right][/tex]

If I do the same I obviously get the same factorization as in the book.

If I choose a permutation matrix,

P = [tex]\left[ \begin{array}{ccc} 0 & 0 & 1 \\ 1 & 0 & 0 \\ 0 & 1 & 0 \end{array} \right][/tex]

I do not get the same factorization. Should I get the same answers even though I'm arranging the equations somewhat different, or am I missing something here?

Help is greatly appreciated, thanks!
 
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If LU decomposition is performed with pivoting, P is the outcome of the decomposition process depending on pivoting. So, it seems odd that you or the author would be choosing P up front.

Maybe you are trying to study the affect on LU w/o pivoting by swapping rows of the original matrix? In any event, I would think using different P's would result in different LU factorizations because the matrix to be factored changes. I don't think two different matrices can have the same LU decomposition.
 
Hi,

Say that I want to do elimination on the above matrix A.
As one possibility, I could start by exchanging row 1 with row 3 such that the integer 2 is in the first pivot position.

I would then perform elimination until I have a upper triangular matrix U.
I get the matrix U by multiplying A with a permutation matrix P, and two elementary matrices, say E and F.

[tex]U = FEPA[/tex]

Then L would be the product of the inverse of E and F.

[tex]L= E^{-1}F^{-1}[/tex]

I could also have started the elimination process by exchanging row 1 with row 2, which would have yielded a different permutation matrix, and also a different factorization LDU.

Am I totally off here?

Thank you for your time!
 
Correct, you'd have two different LDU factorizations because you are factoring two different matrices. Even though you are starting from the same matrix in your two scenarios, the input to the LDU factorization algorithm is a different permutation of the original matrix in each case.

What makes this a bit confusing is your use of the permutation matrix P. Like I said, P is usually determined by the LU decomposition algorithm with pivoting, not something you choose ahead of time. Though perfectly valid, what you are doing is permuting the matrix with a P of your choice before performing LU decomposition w/o pivoting.
 
Last edited:
I understand, thank you :)
 

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