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Systems of Linear Algebraic Equations lecture 4

الكلية كلية العلوم للبنات     القسم قسم فيزياء الليزر     المرحلة 3
أستاذ المادة نزار سالم شنان الزبيدي       4/27/2011 6:51:59 AM

Systems of Linear Algebraic Equations

Nizar Salim / Lecture

1.3.3 Gauss-Jordan Elimination

Gauss-Jordan elimination is a variation of Gauss elimination in

which the elements above the major diagonal are eliminated (made zero)

as well as the elements below the major diagonal. The A matrix is

transformed to a diagonal matrix. The rows are usually scaled to yield

unity diagonal elements, which transforms the A matrix to the identity

matrix, I. the transformed b vector is the solution vector x.

Example 9

Using Gauss-Jordan elimination, to find x1, x2, x3, in equation (1.2)

80x1 20x2 20x3 = 20

- 20x1 + 40x2 20x3 = 20

- 20x1 - 20x2 + 130x3 = 20

Solution

/ 80

20

20

20

20 20 130

20 40 20

80 20 20 1 R

Scaling row1 to give a11=1

3 1

2 1

( 20)

( 20)

20

20

1/ 4

20 20 130

20 40 20

1 1/ 4 1/ 4

R R

R R

/ 35

25

25

1/ 4

0 25 125

0 35 25

1 1/ 4 1/ 4

2 R

3 2

1 2

( 25)

( 1/ 4)

25

5 / 7

1/ 4

0 25 125

0 1 5 / 7

1 1/ 4 1/ 4

R R

R R

Systems of Linear Algebraic Equations

Nizar Salim / Lecture

300/ 7 /(750/ 7)

5/ 7

3/ 7

0 0 750/ 7

0 1 5/ 7

1 0 3/ 7

3 R

2 3

1 3

( 5 / 7)

( 3/ 7)

2 / 5

5 / 7

3/ 7

0 0 1

0 1 5 / 7

1 0 3/ 7

R R

R R

0.40

1.00

0.60

0 0 1

0 1 0

1 0 0

The matrix has been transformed to the identity matrix I and the b vector

has been transformed to the solution vector, x

XT =[ 0.60 1.00 0.40 ]

1.4 Matrix inverse by Gauss-Jordan elimination

The inverse of a square matrix A is the matrix A-1 such that

A A-1 =A-1 A=I Gauss-Jordan elimination can be used to evaluate the

inverse of matrix A by augmenting A with the identity matrix I and

applying the Gauss-Jordan algorithm. The transformed matrix A is the

identity matrix I, and the transformed identity matrix is the matrix

inverse, A-1. thus, applying Gauss-Jordan elimination yields.

[A | I ] »» [I | A-1] ________________(1.23)

Example 10

Find the inverse of matrix A by using Gauss-Jordan elimination

Where

20 20 130

20 40 20

80 20 20

A

Systems of Linear Algebraic Equations

Nizar Salim / Lecture

Solution

0 0 1

0 1 0

1 0 0

20 20 130

20 40 20

80 20 20

A

Performing Gauss-Jordan elimination

1/ 250 1/150 7 / 750

1/100 1/ 30 1/150

2/5 1/100 1/ 250

0 0 1

0 1 0

1 0 0

0.004000 0.006667 0.009333

0.010000 0.033333 0.006667

0.016000 0.010000 0.004000

1 / 250 1 / 150 7 / 750

1 / 100 1 / 30 1 / 150

2 / 125 1 / 100 1 / 250

A 1

The matrix inverse method

The system of linear algebraic equations can be solved by using the

matrix inverse, A-1 consider the general system of linear algebraic

equations:

Ax=b _____________(1.24)

Multiplying (1.24) by A-1 yields

AA-1x=A-1b

Ix=A-1b

x=A-1b _________________(1.25)

Thus, when the matrix inverse A-1 of the coefficient matrix A is

known, the solution vector x is simply the product of the matrix inverse

A-1 and the right-hand-side vector b.

Not all matrices have inverses singular matrices, that is matrices whose

determinant is zero, do not have inverses.

Systems of Linear Algebraic Equations

Nizar Salim / Lecture

Systems of Linear Algebraic Equations

Nizar Salim / Lecture

Systems of Linear Algebraic Equations

Nizar Salim / Lecture

Example 11

Solve the linear system considered in example (10) using the matrix

inverse method.

Solution

20

20

20

1 / 250 1 / 150 7 / 750

1 / 100 1 / 30 1 / 150

2 / 125 1 / 100 1 / 250

x A 1b

x1=(2/125)(20) + (1/100)(20) + (1/250)(20)=0.60

x2=(1/100)(20) + (1/30)(20) + (1/150)(20)=1.00

x3=(1/250)(20) + (1/150)(20) + (7/750)(20)=0.04

Thus xT=[0.60 1.00 0.04]

1.5 Pitfalls of Elimination Method

All nonsingular system of linear algebraic equations have a solution.

In theory, the solution can always be obtained by Gauss elimination.

However, there are two major pitfalls in the application of Gauss

elimination (a)the presence of round-off errors, and (b)ill-condition

systems.

1.5.1 Round-off Errors

Round-off errors occur when exact infinite precision numbers are

approximated by finite precision numbers. The effects of round-off errors

are illustrated in the following example.

Example 12 Effects of round-off errors.

Consider the fallowing system of linear algebraic equation:

0.0003x1+3x2=1.0002 -------------------------------(1.26)

x1+x2 =1

Solve this equation by Gauss elimination, thus

1 / 0.0003

1.0002

1 1

0.0003 3

2 1 R R

-----------------------------(1.27)

Systems of Linear Algebraic Equations

Nizar Salim / Lecture

0.0003

1.0002

1

1.0002

0 9999

0.0003 3

-----------(1.28)

3

1

9999

0.0003

0.9999

9999

0.0003

0.0003 1.0002

9999

0.0003

1.0002

1

2 x ---------(1.29)

3

2

0.0003

0.0002

0.0003

1.0002 3(1/3)

0.0003

1.0002 3 2

1

x

x ----------(1.30)

9999

0.0003

1.0002

1

2 x

0.0003

1.0002 3 2

1

x

x ------------(1.31)

The results are presented in table 1.1

Table 1.1 Solution of eq. (1.31)

Precision x2 x1

3 0.333 3.33

4 0.3333 1.333

5 0.33333 0.70000

6 0.333333 0.670000

7 0.3333333 0.6670000

8 0.33333333 0.66670000

Lets rework the problem by interchanging rows 1 and 2 in eq.(1.26)

x1+x2 =1

0.0003x1+3x2=1.0002 -------------------------------(1.32)

By Gauss elimination

2 1 1.0002 0.0003

1

0.0003 3

1 1

R R

------------------------(1.33)

0.9999

1

0 2.9997

1 1

-------------------------(1.34)

2 1 2 1

2.9997

0.9999

x and x x -------------------------(1.35)

Systems of Linear Algebraic Equations

Nizar Salim / Lecture

Lets solve eq.(1.35) using finite arithmetic. The results are presented in

Table 1.2

Table 1.2 Solution of equation (1.35)

precision x2 x1

3 0.333 0.667

4 0.3333 0.6667

5 0.33333 0.66667

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