vault backup: 2026-10-05 08:42:54
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@@ -15,8 +15,10 @@
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- Gaussian Elimination
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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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- Very important method for many applications, used to solve systems of linear equations
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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 free variables)
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- The first non-zero term in a row
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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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@@ -27,4 +29,10 @@
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- when the $b_{n}$ term of each equation is zero
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- There is a "trivial solution" where each variable equals zero
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- There can also be non-trivial solutions
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-
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$$\begin{bmatrix}
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3 & 6 & 2 \\ h & 12 & k
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\end{bmatrix} \sim \begin{bmatrix}
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\end{bmatrix}$$
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