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Elimination methods for systems of linear equations
- Purpose: find all solutions (x, y, z, …) to linear systems. Methods include substitution, elimination, and matrix-based approaches (Gaussian elimination and Gauss–Jordan elimination).
Substitution and elimination (two-equation example)
- Example system (from transcript):
- Elimination approach (combine equations to remove a variable):
- Multiply the first equation by 3 to align x with the second:
- Subtract the second equation from this result: ⇒ ⇒
- Substitute back into : ⇒
- Augmented-matrix representation (Gaussian elimination):
- Row operation: gives
- Solve: ; then .
- Summary: Simple two-equation elimination yields a unique solution (x, y) = (2, 1).
Note: The transcript also shows other two-equation manipulations (e.g., replacing one equation by a linear combo) to illustrate that different sequences of eliminations lead to the same solution.
Gauss–Jordan elimination (row operations and augmented matrices)
- Core idea: transform the augmented matrix of a linear system to reduced row echelon form (RREF) using elementary row operations.
- Elementary row operations:
- Swap two rows: Ri j
- Multiply a row by a nonzero scalar: Ri ← cRi, c ≠ 0
- Add a multiple of one row to another row: Ri ← Ri + cR_j, c ∈ R
- Example system (from transcript):
- x + 2y + z = 8
- x + y + z = 8
- 3x + y − 2z = 9
- Gauss–Jordan steps (illustrative path to solution):
- R2 ← R2 − R1 → [0, −1, 0 | 0]
- R3 ← R3 − 3R1 → [0, −5, −5 | −15]
- R2 ← −R2 → [0, 1, 0 | 0]
- R3 ← R3 + 5R2 → [0, 0, −5 | −15]
- R3 ← −R3/5 → [0, 0, 1 | 3]
- R1 ← R1 − R3 → [1, 2, 0 | 5]
- R1 ← R1 − 2R2 → [1, 0, 0 | 5]
- Final RREF gives the solution:
- Takeaways:
- Ga