Linear Algebra - Elimination Matrix when Permutation Needed

In summary, the question is whether the permutation matrix used in the elimination process should also be multiplied with the final elimination matrix when finding the reduced row echelon form of a matrix. The answer is yes, the permutation matrix should also be included in the multiplication.
  • #1
YoshiMoshi
226
8

Homework Statement



I feel like I should know the answer to this, so I believe this to be an easy question. Say have matrix A, and I store the elimination matrices E_1,1 E_2,1 etc. and somewhere in the elimination process I have to use a permutation matrix to swap rows. My question is when I find the the final elimination matrix in which I multiply together all elimination matrices I used to get down to reduce row echelon form, do I also multiply by the permutation matrix?

Example:
I have [A] and than I multiply by E_1,1.
Then I multiply by E_2,1
Then I multiply by P_4,3 and am now in reduce row ecehlon form
when I go to find E is it
E = P_4,3 * E_2,1 * E_1,1
or is it just
E = E_2,1 * E_1,1

Thanks for any help.

Homework Equations

The Attempt at a Solution

 
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  • #2
YoshiMoshi said:

Homework Statement



I feel like I should know the answer to this, so I believe this to be an easy question. Say have matrix A, and I store the elimination matrices E_1,1 E_2,1 etc. and somewhere in the elimination process I have to use a permutation matrix to swap rows. My question is when I find the the final elimination matrix in which I multiply together all elimination matrices I used to get down to reduce row echelon form, do I also multiply by the permutation matrix?

Example:
I have [A] and than I multiply by E_1,1.
Then I multiply by E_2,1
Then I multiply by P_4,3 and am now in reduce row ecehlon form
when I go to find E is it
E = P_4,3 * E_2,1 * E_1,1
or is it just
E = E_2,1 * E_1,1

Thanks for any help.

Homework Equations

The Attempt at a Solution


Since you needed to multiply by ##P_{43}## to get the final echelon form, the correct ##E## is the first one you wrote. Try it and see for yourself in an example.
 
  • #3
That's what my gut was telling me. Thanks for your help.
 

1. What is a permutation matrix in linear algebra?

A permutation matrix is a square matrix that is used to represent the rearrangement of rows or columns in another matrix. It is a special type of matrix with exactly one entry of 1 in each row and column, and 0s everywhere else. Permutation matrices are used in linear algebra to simplify matrix operations, such as elimination, by reordering rows or columns.

2. When is a permutation matrix needed in the elimination process?

A permutation matrix is needed in the elimination process when the pivot element (the leading coefficient of a row) is 0. In order to continue with the elimination process, the pivot element must be non-zero. A permutation matrix is used to swap rows in the original matrix, effectively changing the pivot element to a non-zero value and allowing the elimination process to continue.

3. How is a permutation matrix used in solving systems of linear equations?

In solving systems of linear equations, a permutation matrix is used to transform the original system into an equivalent system with a triangular or upper triangular matrix. This simplifies the process of finding the solution to the system. The permutation matrix is applied to both the coefficient matrix and the constant vector, and the resulting system can be solved using back substitution.

4. Can a permutation matrix be used in any type of matrix operation?

No, a permutation matrix is only used in matrix operations that involve elimination, such as Gaussian elimination or LU decomposition. It cannot be used in operations such as matrix multiplication or finding inverses.

5. Are there any properties of permutation matrices that make them useful in linear algebra?

Yes, permutation matrices have several useful properties in linear algebra. They are orthogonal, meaning that their inverse is equal to their transpose, which simplifies calculations. They also have a determinant of either 1 or -1, making them easy to work with in terms of determinants. Additionally, they are used in LU decomposition to find the determinant of a matrix and to solve systems of linear equations.

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