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(1)
(2)

Any straight line in xy-plane can be

represented algebraically by an equation

of the form:

ax + by = c

General form: define a

linear equation

in

the

n

variables :

Where and b are real constants. The variables in a linear equation are sometimes

called unknowns.

Any straight line in xy-plane can be

represented algebraically by an equation

of the form:

General form: define a

linear equation

in

the

n

variables :

◦ Where and b are real constants. ◦ The variables in a linear equation are sometimes

called unknowns.

n

x

x

x

1

,

2

,...,

b

x

a

x

a

x

a

1 1

2 2

...

n n

,

,...,

,

2

1

a

a

n
(3)

The equations and

are linear.

Observe that a linear equation does not involve any

products or roots of variables. All variables occur

only to the first power and do not appear as

arguments for trigonometric, logarithmic, or

exponential functions.

The equations sin x +cos x = 1, log x = 2

are

not

linear.

,

1

3

2

1

,

7

3

y

y

x

z

x

7 3

2 2 3 4

1  xxx

x

The equations and

are linear.

Observe that a linear equation does not involve any

products or roots of variables. All variables occur

only to the first power and do not appear as

arguments for trigonometric, logarithmic, or

exponential functions.

The equations sin x +cos x = 1, log x = 2

(4)

Find the solution of

Solution(a)

we can assign an arbitrary value to x and solve

for y , or choose an arbitrary value for y and solve

for x .If we follow the first approach and assign x

an arbitrary value ,we obtain

arbitrary numbers are called parameter. for example

1 2

4 ) a

( xy

Find the solution of

Solution(a)

we can assign an arbitrary value to x and solve

for y , or choose an arbitrary value for y and solve

for x .If we follow the first approach and assign x

an arbitrary value ,we obtain

◦ arbitrary numbers are called parameter. ◦ for example

2 2

1

1 ,

4 1 2

1 or

2 1 2

, y t x t y t

t

x      

2 , 1

t

t

2 11 as

2 11 ,

3 solution

the yields

3 2

1  xyt

(5)

◦ A solution of a linear equation is a sequence of n numbers

s1, s2, ..., sn such that the equation is satisfied. The set of all solutions of the equation is called its solution set or general solution of the equation

A solution of a linear equation is a sequence of n numbers

(6)

Find the solution of

Solution(b)

we can assign arbitrary values to any two

variables and solve for the third variable.

for example

where s, t are arbitrary values

. 5 7

4

(b) x1x2x3

Find the solution of

Solution(b)

we can assign arbitrary values to any two

variables and solve for the third variable.

for example

where s, t are arbitrary values

x s t x s x t

 

 

2 3

(7)

A finite

set

of linear equations

in the variables

is called a

system of linear

equations

or a

linear system

.

A sequence of numbers

is called a

solution

of the system.

A system has

no

solution is

said to be

inconsistent

; if

there is

at least

one solution

of the system, it is called

consistent

.

n

x

x

x

1

,

2

,...,

n n

n n

b

x

a

x

a

x

a

b

x

a

x

a

x

a

...

...

2 2

2 22 1

21

1 1

2 12 1

11

A finite

set

of linear equations

in the variables

is called a

system of linear

equations

or a

linear system

.

A sequence of numbers

is called a

solution

of the system.

A system has

no

solution is

said to be

inconsistent

; if

there is

at least

one solution

of the system, it is called

consistent

.

n

s

s

s

1

,

2

,...,

a

m

x

a

m

x

a

mn

x

n

b

m

...

2 2 1

1

(8)

Every system of linear equations has

either no solutions, exactly one

solution, or infinitely many solutions.

A general system of two linear

equations:

(Figure1.1.1)

Two lines may be parallel -> no solution

Two lines may intersect at only one point -> one solution

Two lines may coincide

-> infinitely many solution

Every system of linear equations has

either no solutions, exactly one

solution, or infinitely many solutions.

A general system of two linear

equations:

(Figure1.1.1)

◦ Two lines may be parallel -> no solution

◦ Two lines may intersect at only one point -> one solution

◦ Two lines may coincide

-> infinitely many solution

zero) both

not ,

(

zero) both

not ,

(

2 2 2 2

2

1 1 1 1

1

b a c y b x a

b a c y b x a

 

(9)

n n n n b x a x a x a b x a x a x a b x a x a x a             ... ... ... 2 2 1 1 2 2 2 22 1 21 1 1 2 12 1 11    

 The location of the +’s,

the xs, and the =s can be abbreviated by writing only the rectangular array of numbers.   m n mn m

m x a x a x b

a    

        ... 2 2 1 1                 m mn m m n n b a a a b a a a b a a a ... ... ... 2 1 2 2 22 21 1 1 12 11      of numbers.

 This is called the

augmented matrix for the system.

 Note: must be written in

the same order in each equation as the unknowns and the constants must be on the right.

1th column

(10)

 The basic method for solving a system of linear equations

is to replace the given system by a new system that has the same solution set but which is easier to solve.

 Since the rows of an augmented matrix correspond to the

equations in the associated system. new systems is generally obtained in a series of steps by applying the

following three types of operations to eliminate unknowns systematically. These are called elementary row

operations.

1. Multiply an equation through by an nonzero constant. 2. Interchange two equation.

3. Add a multiple of one equation to another.

 The basic method for solving a system of linear equations

is to replace the given system by a new system that has the same solution set but which is easier to solve.

 Since the rows of an augmented matrix correspond to the

equations in the associated system. new systems is generally obtained in a series of steps by applying the

following three types of operations to eliminate unknowns systematically. These are called elementary row

operations.

1. Multiply an equation through by an nonzero constant. 2. Interchange two equation.

(11)

0 5 6 3 7 1 7 2 9 2          z y x z y z y x

to thesecond equation first the times 2 -add 1 3 4 2 9 2          z y x z y x

to the third

equation first the times 3 -add

to thesecond

0 5

6

3   

      z y x             0 5 6 3 1 3 4 2 9 2 1 1

0

5

6

3

17

7

2

0

9

2

1

1

to the third

to the third row first the times 3 -add

(12)

0 11 3 9 2 2 17 2 7         z y z y z y x

2 1 by equation second the multiply 17 7 2 9 2          z y z y x

to the third

equation second the times 3 -add

2 27 11

3          z y               27 11 3 0 17 7 2 0 9 2 1 1

27

11

3

0

1

0

9

2

1

1

2 17 2 7

to the third

(13)

3 9 2 2 17 2 7        z z y z y x

equation by-2 third the Multiply 2 17 2 7

9

2

z

y

z

y

x

to the first

equation second the times 1 -Add

2 3 2 1 2 2

z

z

y

              2 3 2 1 2 17 2 7 0 0 1 0 9 2 1 1

3

1

0

0

1

0

9

2

1

1

2 17 2 7

to the first

to the first row second the times 1 -Add

rowby-2

third e

(14)

3 2 1    z y x

to thesecond equation third the times and first the to equation third the times -Add 2 7 2 11

3

2 17 2 7 2 35 2 11

z

z

y

z

x

3

z

            3 1 0 0 1 0 0 1 2 17 2 7 2 35 2 11

3

1

0

0

2

0

1

0

1

0

0

1

to the second

row third the times and first the to row third the times -Add 2 7 2 11

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