By means of a finite sequence of elementary row operations, called Gaussian elimination, any matrix can be transformed to a row echelon form. This transformation is necessary for solving a system of linear equations.
Before getting into more detail, there are a couple of key terms that should be mentioned:
- Augmented matrix: an augmented matrix is a matrix obtained by appending the columns of two given matrices, usually for the purpose of performing the same elementary row operations on each of the given matrices.
- Upper triangle form: A square matrix is called upper triangular if all the entries below the main diagonal are zero. A triangular matrix is one that is either lower triangular or upper triangular. A matrix that is both upper and lower triangular is a diagonal matrix.
- Elementary row operations: Swap rows, add rows or multiply rows.
Gaussian Elimination
- Write the augmented matrix for the linear equations.
- Use elementary row operations on the augmented matrix
$[A|b]$ to transform$A$ to upper triangle form. If a zero is on the diagonal, switch the rows until a nonzero is in its place. - Use back substitution to find the solution.
Example 1: Solve the system by Gaussian Elimination:
Write the augmented matrix:
Use elementary row operations to reduce the matrix to reduced row echelon form:
Using elementary row operations to obtain reduced row echelon form ('rref' in the calculator) the solution to the system is revealed in the last column: