Solve LU Decomposition for Matrix 0 0 1, 1 0 0, 0 1 0

In summary, the conversation discusses the process of decomposing a given matrix using LU decomposition. The person initially attempts to use row operations to make the matrix upper and lower triangular, but ends up with the identity matrix and a zero matrix. Another person then suggests that the original decomposition is correct and explains how to find the permutation matrix. The conversation concludes with a clarification on the roles of L, U, and P in LU decomposition.
  • #1
emira
7
0

Homework Statement


0 0 1
1 0 0
0 1 0 decompose this matrix using LU decomposition.


Homework Equations





The Attempt at a Solution



I took this matrix and augmented it with a zero (3 by 3) matrix. Then I performed the same row operations on both...the row operations with the purpose of making the matrix I was given an upper triangular matrix, and the zero matrix a lower triangular matrix. I ended up just switching rows twice and got the identity matrix for the upper matrix and got the matrix zero for the lower matrix...so no result. Does anyone know any other method I could use to solve this problem?

Thank you,
emira
 
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  • #2
I believe your original LU decomposition is correct. This is a very trivial decomposition, since it is just a permuted identity matrix.
 
  • #3
But the product of the identity matrix with matrix zero is matrix zero, thus not giving me the matrix i started with. does that it mean the matrix is not decompos-able?
 
  • #4
Well, I'm not quite sure how you would have learned how to do LU decomposition, but both your upper and lower triangular matrices should have diagonals non-zero, one of which is usually normalized to be all 1's. Furthermore there is a permutation matrix (especially if you're doing anything computational).

For example, if A is the matrix you're trying to put in LU decomposition, then you find L, U and P such that LUP = A.

Thus let [itex] A = \begin{bmatrix} 0 & 0 & 1 \\ 1 & 0 & 0 \\ 0 & 1 & 0 \end{bmatrix} [/itex]

Then L and U are identity, and P = A (the original matrix).

Edit: Obviously, where L is lower triangular, U is upper triangular, and P is a permuted identity matrix
 

FAQ: Solve LU Decomposition for Matrix 0 0 1, 1 0 0, 0 1 0

What is LU decomposition?

LU decomposition is a method used to factorize a square matrix into a lower triangular matrix (L) and an upper triangular matrix (U). It is often used in numerical analysis and linear algebra to solve systems of linear equations.

Why is LU decomposition useful?

LU decomposition allows for more efficient and accurate solutions to systems of linear equations compared to traditional methods such as Gaussian elimination. It also allows for easier computation of determinants and inverses of matrices.

How is LU decomposition performed?

The LU decomposition algorithm involves decomposing a matrix A into a product of an upper triangular matrix U and a lower triangular matrix L. This is typically done using Gaussian elimination or its variants, such as Doolittle's method or Crout's method.

What are the applications of LU decomposition?

LU decomposition has numerous applications in various fields such as engineering, physics, economics, and computer science. It is used in solving linear systems of equations, finding determinants and inverses of matrices, and in machine learning algorithms.

What are the limitations of LU decomposition?

LU decomposition can only be performed on square matrices and may not be feasible for large matrices with many non-zero elements. It also may not work if the matrix is singular or ill-conditioned. In such cases, other methods such as singular value decomposition may be more suitable.

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