Eng.Ansam Hadi Rashed
GAUSSIAN
ELIMINATION
2019
Al- Mustansiriya university
college of engineering
Computer Department
“Mathematics is the door and key
to the sciences. Roger Bacon”
Gaussian elimination
(also called row reduction) is a method used to solve systems of linear equations. It
is named after Carl Friedrich Gauss, a famous German
mathematician who wrote about this method,
Gaussian elimination include two methods
• Without pivot
• With pivot
Solving the linear system without pivot
We denote this linear system by Ax = b.
The augmented matrix
for this system is
Solving the linear system
1- eliminate x1 from equations 2, 3, and 4
R2=R2-2R1 M2,1=2
R3=R3+R1 M3,1=-1
R4=R4-2R1 M4,1=2
This will introduce zeros into the positions
below the diagonal in column 1, yielding
Solving the linear system
2- eliminate x2 from equations 3 and 4
R3=R3-2R2 M3,2=2
R4=R4-3R2 M4,2=3
This reduces the augmented matrix to
Solving the linear system
2- eliminate x3 from equation 4
R4=R4+R3 M4,3=-1
This reduces the augmented matrix to
Ms values take revers sign
Solving the linear system
3- Return this to the familiar linear system
Solving the linear system
There is a surprising result involving matrices associated with this
elimination process
U which resulted from the
elimination process.
L the lower triangular matrix constructed from M values ..
A = LU
when the process of Gaussian elimination without pivoting is applied to solving
a linear system Ax = b, we obtain A = LU
Solving linear system using LU Decomposition method
A = LU


Solving linear system using LU Decomposition method
 This implies
Solving linear system using LU Decomposition method
Ax=b A=LU
LUx=b
Ly=b
Solving linear system using LU Decomposition method
Ax=b A=LU
LUx=b to find Xs Ly=b && Ux=y
Example : Solve the following system of linear equations, by LU decomposition
method
Sol:
A=LU
LU
=L33
Therefore, we get,
Now, let , then implies L y =b U x=y
Gaussian
Gaussian
In the case in which partial pivoting is used P as a permutation matrix.
For example , consider
The matrix P A is obtained from A by switching around rows of A
The result LU = P A means that the LU - factorization is valid for the matrix A with its
rows suitably permuted.
Solving linear system with pivot
Gaussian
Solving the linear system with pivot
Gaussian
Gaussian
OPERATIONS COUNT
2019
THANK YOU
ANY QUESTION??

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Gaussian

  • 1. Eng.Ansam Hadi Rashed GAUSSIAN ELIMINATION 2019 Al- Mustansiriya university college of engineering Computer Department “Mathematics is the door and key to the sciences. Roger Bacon”
  • 2. Gaussian elimination (also called row reduction) is a method used to solve systems of linear equations. It is named after Carl Friedrich Gauss, a famous German mathematician who wrote about this method, Gaussian elimination include two methods • Without pivot • With pivot
  • 3. Solving the linear system without pivot We denote this linear system by Ax = b. The augmented matrix for this system is
  • 4. Solving the linear system 1- eliminate x1 from equations 2, 3, and 4 R2=R2-2R1 M2,1=2 R3=R3+R1 M3,1=-1 R4=R4-2R1 M4,1=2 This will introduce zeros into the positions below the diagonal in column 1, yielding
  • 5. Solving the linear system 2- eliminate x2 from equations 3 and 4 R3=R3-2R2 M3,2=2 R4=R4-3R2 M4,2=3 This reduces the augmented matrix to
  • 6. Solving the linear system 2- eliminate x3 from equation 4 R4=R4+R3 M4,3=-1 This reduces the augmented matrix to Ms values take revers sign
  • 7. Solving the linear system 3- Return this to the familiar linear system
  • 8. Solving the linear system There is a surprising result involving matrices associated with this elimination process U which resulted from the elimination process. L the lower triangular matrix constructed from M values ..
  • 9. A = LU when the process of Gaussian elimination without pivoting is applied to solving a linear system Ax = b, we obtain A = LU
  • 10. Solving linear system using LU Decomposition method A = LU  
  • 11. Solving linear system using LU Decomposition method  This implies
  • 12. Solving linear system using LU Decomposition method Ax=b A=LU LUx=b Ly=b
  • 13. Solving linear system using LU Decomposition method Ax=b A=LU LUx=b to find Xs Ly=b && Ux=y
  • 14. Example : Solve the following system of linear equations, by LU decomposition method Sol: A=LU
  • 16. Therefore, we get, Now, let , then implies L y =b U x=y
  • 19. In the case in which partial pivoting is used P as a permutation matrix. For example , consider The matrix P A is obtained from A by switching around rows of A The result LU = P A means that the LU - factorization is valid for the matrix A with its rows suitably permuted. Solving linear system with pivot
  • 21. Solving the linear system with pivot