Download Introduction to Database Systems

System of Linear Equations
and Augmented Matrices
Dr .Hayk Melikyan
Departmen of Mathematics and CS
[email protected]
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It is impractical to solve more complicated linear systems by
hand. Computers and calculators now have built in routines to
solve larger and more complex systems.
Matrices, in conjunction with graphing utilities and or
computers are used for solving more complex systems. In this
section, we will develop certain matrix methods for solving
two by two systems.
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Matrices

A matrix is a rectangular
array of numbers written
within brackets. Here is an
example of a matrix which
has three rows and three
columns: The subscripts
give the “address” of each
entry of the matrix. For
example the entry 23
Is found in the second row
and third column
a

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 a11 a12

a
a
21
22

a
 31 a32
a13 

a23 

a33 
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MATRICES
A MATRIX is a rectangular array of numbers written within
brackets.
Each number in a matrix is called an ELEMENT. If a matrix
has m rows and n columns, it is called an m x n MATRIX;
m x n is the SIZE; m and n are the DIMENSIONS.
A matrix with n rows and n columns is a SQUARE MATRIX
OF ORDER n.
A matrix with only one column is a column matrix; a matrix
with only one row is a ROW MATRIX. The element in the ith
row and jth column of a matrix A is denoted aij.
The PRINCIPAL DIAGONAL of a matrix A consists of the
elements a11, a22, a33, ….
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Matrix solutions of linear systems

When solving systems of
linear equations, the
coefficients of the variables
played an important role. We
can represent a linear system
of equations using what is
called an augmented matrix,
a matrix which stores the
coefficients and constants of
the linear system and then
manipulate the augmented
matrix to obtain the solution
of the system. Here is an
example:
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

x +3y=5
2x – y=3
 1 3 5


 2 1 3
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Generalization

Linear system:

Associated augmented
matrix:
a11 x1  b11 y1  k1  a11

a21 x1  b21 x2  k2 a21

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a12 k1 

a22 k2 
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Operations that Produce Row-Equivalent Matrices:

1. Two rows are interchanged:
Ri  R j

2. A row is multiplied by a nonzero constant:
kRi  Ri

3. A constant multiple of one row is added to
another row:
kR j  Ri  Ri
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Solve using Augmented matrix:
Solve
 x +3y=5
 2x – y=3






1. Augmented system
2. Eliminate 2 in 2nd row by row
operation
3. Divide row two by -7 to obtain
a coefficient of 1.
4. Eliminate the 3 in first row,
second position.
5. Read solution from matrix
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
:
1 3 5


2

1
3


2 R1  R2 
1 3 5 


0

7

7


R2 /  7  R2 
1 3 5


0
1
1


3R2  R1  R1 
1 0

0 1
2
  x  2, y  1; (2,1)
1
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Solving a system using augmented matrix methods


1.
2.
3.
4.
5.
6.
7.
x+2y=4
x+(1/2)y=4
Eliminate fraction in second
equation.
Write system as augmented
matrix.
Multiply row 1 by -2 and add to
row 2
Divide row 2 by -3
Multiply row 2 by -2 and add to
row 1.
Read solution : x = 4, y = 0
(4,0)
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x  2y  4
1
y  4  2x  y  8
2
1 2 4 


2
1
8


x
1

0
1

0
1

0
2 4

3 0 
2 4

1 0
0 4

1 0
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Solving a system using augmented matrix methods
10x -2y=6
-5x+y= -3




1. Represent as augmented matrix.
2. Divide row 1 by 2
3. Add row 1 to row 2 and replace row 2
by sum
4. Since 0 = 0 is always true, we have a
dependent system. The two equations
are identical and there are an infinite
number of solutions.
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10 2 6 


  5 1 3 
 5 1 3 


  5 1 3 
 5 1 3 


0
0
0


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Another example

Solve
5 x  2 y  7
5
y  x 1
2

Rewrite second equation :
2 y  5x  2 
5 x  2 y  2

5 x  2 y  7 

5 x  2 y  2 
 5 2 7 


 5 2 2 
5 2 7 


0 0 5 
Since we have an impossible equation,
there is no solution. The two lines are
parallel and do not intersect.
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Recall
A system of linear equations is transformed into an
equivalent system if:
(a) two equations are interchanged;
(b) an equation is multiplied by a nonzero constant;
(c) a constant multiple of one equation is added to
another equation
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Given the system of linear equations (I) and its associated
augmented matrix (II).
If (II) is row equivalent to a matrix of the form
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