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Home > Matrix & Vector calculators > LU Decomposition using Gauss Elimination method of Matrix example
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8. LU decomposition using Gauss Elimination method of matrix example
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- Example `[[8,-6,2],[-6,7,-4],[2,-4,3]]`
- Example `[[3,2,4],[2,0,2],[4,2,3]]`
- Example `[[1,1,1],[-1,-3,-3],[2,4,4]]`
- Example `[[2,3],[4,10]]`
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Other related methods
- Transforming matrix to Row Echelon Form (ref)
- Transforming matrix to Reduced Row Echelon Form (rref)
- Rank of matrix
- Characteristic polynomial of matrix
- Eigenvalues
- Eigenvectors (Eigenspace)
- Triangular Matrix
- LU decomposition using Gauss Elimination method of matrix
- LU decomposition using Doolittle's method of matrix
- LU decomposition using Crout's method of matrix
- Diagonal Matrix
- Cholesky Decomposition
- QR Decomposition (Gram Schmidt Method)
- QR Decomposition (Householder Method)
- LQ Decomposition
- Pivots
- Singular Value Decomposition (SVD)
- Moore-Penrose Pseudoinverse
- Power Method for dominant eigenvalue
- Inverse Power Method for dominant eigenvalue
- Determinant by gaussian elimination
- Expanding determinant along row / column
- Determinants using montante (bareiss algorithm)
- Leibniz formula for determinant
- determinants using Sarrus Rule
- determinants using properties of determinants
- Row Space
- Column Space
- Null Space
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1. Example `[[8,-6,2],[-6,7,-4],[2,-4,3]]`
1. Find LU Decomposition using Gauss Elimination method of Matrix ... `[[8,-6,2],[-6,7,-4],[2,-4,3]]`Solution:`LU` decomposition : If we have a square matrix A, then an upper triangular matrix U can be obtained without pivoting under Gaussian Elimination method, and there exists lower triangular matrix L such that A=LU. | Here `A` | = | | `8` | `-6` | `2` | | | `-6` | `7` | `-4` | | | `2` | `-4` | `3` | |
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Using Gaussian Elimination method `R_2 larr R_2-` `(-0.75)``xx R_1` `[:.L_(2,1)=color{blue}{-0.75}]` | = | | `8` | `-6` | `2` | | | `0` | `2.5` | `-2.5` | | | `2` | `-4` | `3` | |
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`R_3 larr R_3-` `(0.25)``xx R_1` `[:.L_(3,1)=color{blue}{0.25}]` | = | | `8` | `-6` | `2` | | | `0` | `2.5` | `-2.5` | | | `0` | `-2.5` | `2.5` | |
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`R_3 larr R_3-` `(-1)``xx R_2` `[:.L_(3,2)=color{blue}{-1}]` | = | | `8` | `-6` | `2` | | | `0` | `2.5` | `-2.5` | | | `0` | `0` | `0` | |
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| `:.U` | = | | `8` | `-6` | `2` | | | `0` | `2.5` | `-2.5` | | | `0` | `0` | `0` | |
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`L` is just made up of the multipliers we used in Gaussian elimination with 1s on the diagonal. | `:.L` | = | | `1` | `0` | `0` | | | `color{blue}{-0.75}` | `1` | `0` | | | `color{blue}{0.25}` | `color{blue}{-1}` | `1` | |
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Now checking `A=LU` ? | `LU` | = | | `1` | `0` | `0` | | | `-0.75` | `1` | `0` | | | `0.25` | `-1` | `1` | |
| `xx` | | `8` | `-6` | `2` | | | `0` | `2.5` | `-2.5` | | | `0` | `0` | `0` | |
| = | | `8` | `-6` | `2` | | | `-6` | `7` | `-4` | | | `2` | `-4` | `3` | |
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| And `A` | = | | `8` | `-6` | `2` | | | `-6` | `7` | `-4` | | | `2` | `-4` | `3` | |
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Solution is possible.
This material is intended as a summary. Use your textbook for detail explanation. Any bug, improvement, feedback then
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