vault backup: 2026-10-04 11:15:27
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\end{bmatrix} \end{gathered}$$
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- Same elementary operations can be used with augmented matrices, now it is with rows instead of equations.
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- gaussian elimination
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- this is converting a matrix to **echelon form** (or row echel)
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- this is converting a matrix to **echelon form** (or row echelon form)
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- this is when every leading term is a column to the left of the one below it and any zero rows are at the bottom
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- once the augmented matrix is in echelon form it can be converted back into a linear system of equations (that is not in echelon form) and solved
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- the pivot is the coefficient of the leading terms (or the fr)
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- Gauss-Jordan elimination
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- this can make it easier to find the general solution of the system
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- 1. multiply each nonzero row by the inverse of the pivot so every pivot is 1
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