Gauss elimination method is used to solve a system of linear equations. Let’s recall the definition of these systems of equations. A system of linear equations is a group of linear equations with various unknown factors. As we know, unknown factors exist in multiple equations. Solving a system involves finding the value for the unknown factors to verify all the equations that make up the system.
If there is a single solution that means one value for each unknown factor, then we can say that the given system is a consistent independent system. If multiple solutions exist, the system has infinitely many solutions; then we say that it is a consistent dependent system. If there is no solution for unknown factors, and this will happen if there are two or more equations that can’t be verified simultaneously, then we say that it’s an inconsistent system.
This can be summarized in a table as given below:
Name of the system of equations |
Number of solutions |
Consistent independent system |
1 |
Consistent dependent system |
Multiple or Infinitely many |
Inconsistent system |
0 |
Now, let’s have a look at the method that can be used to find the solution(s) of the given system of equations.
What is the gauss elimination method?
In mathematics, the Gaussian elimination method is known as the row reduction algorithm for solving linear equations systems. It consists of a sequence of operations performed on the corresponding matrix of coefficients. We can also use this method to estimate either of the following:
- The rank of the given matrix
- The determinant of a square matrix
- The inverse of an invertible matrix
To perform row reduction on a matrix, we have to complete a sequence of elementary row operations to transform the matrix till we get 0s (i.e., zeros) on the lower left-hand corner of the matrix as much as possible. That means the obtained matrix should be an upper triangular matrix. There are three types of elementary row operations; they are:
- Swapping two rows and this can be expressed using the notation ↔ , for example, R_{2} ↔ R_{3}
- Multiplying a row by a nonzero number, for example, R_{1} → kR_{2} where k is some nonzero number
- Adding a multiple of one row to another row, for example, R_{2} → R_{2} + 3R_{1}
Learn more about the elementary operations of a matrix here.
The obtained matrix will be in row echelon form. The matrix is said to be in reduced row-echelon form when all of the leading coefficients equal 1, and every column containing a leading coefficient has zeros elsewhere. This final form is unique; that means it is independent of the sequence of row operations used. We can understand this in a better way with the help of an example given below.
Gauss Elimination Method with Example
Let’s have a look at the gauss elimination method example with a solution.
Question:
Solve the following system of equations:
x + y + z = 2
x + 2y + 3z = 5
2x + 3y + 4z = 11
Solution:
Given system of equations are:
x + y + z = 2
x + 2y + 3z = 5
2x + 3y + 4z = 11
Let us write these equations in matrix form.
Subtracting R_{1} from R_{2} to get the new elements of R_{2}, i.e. R_{2} → R_{2} – R_{1}.
From this we get,
Let us make another operation as R_{3} → R_{3} – 2R_{1}
Subtract R_{2} from R_{1} to get the new elements of R_{1}, i.e. R_{1} → R_{1} – R_{2}.
Now, subtract R_{2} from R_{3} to get the new elements of R_{3}, i.e. R_{3} → R_{3} – R_{2}.
Here,
x – z = -1
y + 2z = 3
0 = 4
That means, there is no solution for the given system of equations.
Gauss Elimination Method Problems
- Solve the following system of equations using Gauss elimination method.
x + y + z = 9
2x + 5y + 7z = 52
2x + y – z = 0
- Solve the following linear system using Gaussian elimination method.
4x – 5y = -6
2x – 2y = 1
- Using Gauss elimination method, solve:
2x – y + 3z = 9
x + y + z = 6
x – y + z = 2