YOGYAKARTA STATE UNIVERSITY
MATHEMATICS AND NATURAL SCIENCES FACULTY MATHEMATICS EDUCATION STUDY PROGRAM Topic: Linear Systems
An equation of the type a1x1 a2x2 anxn b , (1) expressing b in terms of the variables x1,x2,,xn and the known constants
n a a
a1, 2,, , is called a linear equation. A solution to the linear equation (1) is a sequence of nnumbers s1,s2,,sn, which has the property that (1) is satisfied when x1s1,x2 s2,,xn sn are subtituted in (1).
Example 1: x1 2,x2 3,andx3 4 is a solution to the linear equation 13
4 3
6x1 x2 x3 , because 6(2)3(3)4(4)13. This is not the only solution to the given linear equation, since x1 3,x2 1,dan x3 7 is another solution.
A system of equations that has no solutions is said to be inconsistent; if there is at least one solution of the system, it is called consistent. To illustrate the possibilities that can occur in solving systems of linear equations, consider a general system of two linear equations in the unknowns x and y:
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
The graphs of these equations are lines; call them l1 and l2. Since a point (x, y) lies on a line if and only if the numbers x and y satisfy the equation of the line, the solutions of the system of equations correspond to points of intersection of l1 and l2. There are three possibilities, illustrated in Figure 1:
The lines l1 and l2 may be parallel, in which case there is no intersection and consequently no solution to the system. The lines l1 and l2 may intersect at only one point, in which case the system has exactly one solution. The lines l1 and l2 may coincide, in which case there are infinitely many points of intersection and consequently infinitely many solutions to the system.
Although we have considered only two equations with two unknowns here, we will show later that the same three possibilities hold for arbitrary linear systems Every system of linear equations has no solutions, or has exactly one solution, or has infinitely many solutions.
More generally, a linear system is a system of m linear equations in n unknowns, and can be conveniently denoted by
.
2 2 1
1
2 2
2 22 1
21
1 1
2 12 1 11
m n mn m
m
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)
A solution to a linear system (2) is a sequence of nnumbers s1,s2,,sn, which has the property that each equation in (2) is satisfied when
n n s x s x s
x1 1, 2 2,, are subtituted in (2).
The Solution of The Linear System
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 is easier to solve. This new system is generally obtained in a series of steps by applying the following three types of operations to eliminate unknowns systematically:
The Linear Equation Operation 1. Interchange two equations.
Example 2: Given the linear system:
0 5 6 3
1 3 4 2
9 2
z y x
z y x
z y x
To eliminate x from the second equation, we add (2) times the first equation to the second one to obtain
0 5
6 3
17 3
4
9 2
z y x
z y
z y x
To eliminate x from the second equation, we add (3) times the first equation to the third one to obtain
27 11
3
17 7
2
9 2
z y
z y
z y x
Multiply the second equation with 21 , to obtain
27 11
3
9 2
2 17 2
7
z y
z y
z y x
Added (3) times the second equation to the third one to obtain
2 3 2
1
2 17 2
7
9 2
z z y
z y x
Multiply the third equation with 2 , to obtain
3 9 2
2 17 2
7
z z y
z y
x
Added (1) times the second equation to the first one to obtain
3
2 17 2
7
2 35 2
11
z z y
Added (112 ) times the third equation to the first one and ( 2
7) times the third
equation to the second one to obtain
3 2 1
z y x
We conclude that the solution of the linear system is x1,y2,z 3.
Exercises 1:
1. Which of the following are linear equations in x1,x2 andx3? (a) x1 5x2 2x3 1
(b)x1 3x2 x1x3 2 (c) x1 7x2 3x3 (d)x12 x2 8x3 5 (e) 35 2 2 3 4
1 x x
x
(f) 13
3 2
1 7
3 1
2
x x
x
2. Find the solution set of each of the following linear equations. (a)7x5y 3.
(b) 3x15x2 4x3 7
(c) 8x12x2 5x36x4 1 (d) 3v8w2xy4z 0.
3. Find the solution of given the linear system.
(a)
10 7 4 3
1 2 3
8 2
z y x
z y x
z y x
(b)
0 2
6
7 4 3
1 2
2
z y x
z y x
z x
4. (a) Find a linear equation in the variables x and y that has the general solution t
(b)Show that xt,
2 5 2 1
t
y is also the general solution of the equation in part (a).
5. Consider the system of equations
c z y x
b z x
a z y x
3 2
2
Show that for this system to be consistent, the constant a, b, and c must satisfy c = a + b.
6. Show that if the linear equations x1 kx2 c and x1 lx2 d have the same solution set, then the equations are identical.
7. For which value(s) of the constant k does the system
k y x
y x
2 2
3
have no solutions? Exactly one solution? Infinitely many solutions? Explain your reasoning.
8. Consider the system of equations
m fy ex
l dy cx
k by ax
Indicate what we can say about the relative positions of the lines axbyk, l
dy
cx , and ex fymwhen (a) the system has no solutions.
(b) the system has exactly one solution. (c) the system has infinitely many solutions.
9. If the system of equations in Exercise 8 is consistent, explain why at least one equation can be discarded from the system without altering the solution set. 10. If k = l = m = 0 in Exercise 8, explain why the system must be consistent.
YOGYAKARTA STATE UNIVERSITY
MATHEMATICS AND NATURAL SCIENCES FACULTY MATHEMATICS EDUCATION STUDY PROGRAM Topic: Matrices
Definition 1. An mn matrix A is a rectangular of mn real (or complex) numbers arranged in m horizontal rows and n vertical columns :
mn m
m
n n
a a
a
a a
a
a a
a A
2 1
2 22
21
1 12
11
. (3)
The ith row of A,
ai1 ai2 ain
, (1 i m); the jth column of A,
mj j j
a a a
2 1
,
(1 j n).
If m = n, we say that A is a square matrix of order n, and that the numbers nn
a , , a ,
a11 22 form the main diagonal A. We refer to the number aij, which is in the ith row and jth column of A, and (3) often write as A[aij]. Sum of all main diagonal is called trace A (tr A).
Example 3:
1 0 1
3 2 1
A is an 23 matrix with
. a , a , a ,
a122 13 3 220 23 1
3 2
4 1
B is an 22 matrix, with
). 2 ( ) 3 ( 1 )
(A tr
2 1 1
2 1 3
1 0 2
0 1 1
D is an 33 matrix, with tr(A)3. E
3 is an 11 matrix.
1 0 2
F is an 13 matrix or row matrix.
The Equality of Two Matrices
Definition 2. Two mn matrices A[aij] and B[bij] are said to be equal if ij
ij b
a , 1im,1 j n, that is, if corresponding elements are equal.
Example 4: The matrices
5 4 0
4 3 2
1 2 1
A and
z y
x w B
4 4 2
2 1
are equal if w1,x3,y0 and
5 z .
Matrix Addition
Definition 3. If A = [aij] and B = [bij] are mn matrices, then A+B is a mn matrix C =[cij], defined by cij = aij + bij (1im,1 jn) and the difference between A and B is D = [dij] noted as A(1)B AB, defined by
ij ij ij a b d .
Example 5:
1. Given
3 1 2
4 2 1
A and
1 3 1
4 2 0
B .
Then
4 2 3
0 0 1 1
3 3 1 1 2
) 4 ( 4 2 2 0 1 B
A .
2. If
1 2 4
5 3 2
A and
2 5 3
3 1 2
3 3 1
8 4 0 2 1 5 2 3 4
3 5 1 3 2 2 B
A .
3. Given
14 2
8 4
A ,
4 10
2 6
B and
3 21
4 10
C . Then
21 9
-2 20 3
4 14 21 -10 2
4 -2 -8 10 6 4 C B
A .
Additon Matrix Properties
Given A, B, C, and D are mn matrices. (a) A + B = B + A.
(b) A + (B + C) = (A + B) + C.
(c) A + O = A. O matrix is called zero matrix or the addition identity.
(d) A + D = O. DA is called the inverse addition matrix or the negative of A.
Example 6:
1. Given .
0 0
0 0 O and 3 2
1 4
A Then
3 2
1 4 0 3 0 2
0 1 0 4 O
A = A.
2. Given .
2 5 4
4 3 2
A Then ,
2 5 4
4 3 2
A and we obtained
O A
A( ) .
Scalar Multiplication
Example 7:
Scalar Multiplication Matrix Properties
If r and s are real number and A and B are matrices, then and
Matrix Multiplication and and
and
and -2
have we and
.
tidak sesuai.
Matrix Multiplication Properties If A, B, and C have the suitable size, then and
Then and
The Transpose of Matrix
Definition 6. If A = [aij] is an mn matrix, then AT=
aijT , where ji T ij aExample 12:
2 3
5 2
0 4 then
, 2 5 0
3 2
4 T
A A
3 2 4
4 1 2
0 3 6 then
, 3 4 0
2 1 3
4 2 6
T B B
3 2 4
2 3 5 then
, 3 2
2 3
4 5
T C C
1 5 3 then
, 1 5
3 DT
D
2 1 3
then , 3 1 2
T
E E
The Transpose Properties
If r is scalar number and A and B are matrices, then (a) (AT)T = A. (c) (AB)T = BTAT. (b) (A + B)T = AT + BT. (d) (rA)T = rAT.
Example 13: Given .
1 -3
2 2
1 0 and
3 1 2
2 3 1
B
A
. 3 5
7 12 3 2
1 3
2 1 1 2 1
3 2 0 and
3 5
7 12
Then
T T
T
A B (AB)
Example 14: The matrices are symmetric,
1 0 0
0 1 0
0 0 1 and
6 5 3
5 4 2
3 2 1
3
I
A .
Exercises 2:
1. Suppose that A, B, C, D, and E are matrices with the following sizes: )
5 4 (
A , B(45), C(52), D(42), E(54)
Determine which of the following matrix expressions are defined. For those that are defined, give the size of the resulting matrix.
(a)BA (b)AC + D (c)AE + B (d)AB + B (e)E(A + B) (f)E(AC) (g)ETA (h)(AT + E)D
2. Given r = -4 and .
5 1 2
1 2 4
, 3 1 2
2 3 1
B
A
Show that : (a) (A + B)T = AT + BT (b) (rA)T = rAT.
3. Given
2 1
4 2
1 3 , 3 1 2
2 3 1
B
A . Show that (AB)T = BTAT.
4. Given
. 3 2
0 1 and
, 1 2 3
-3 1 2
2 1 1
2 3
-1 2
, 0 1 3
4 2 1
-3 1 2
, 2 1
4 3
1 2 , 5 2 3
2 1 2
F E
D C
If possible compute :
(a) (AB)T (b) BTAT (c) ATBT (d) BBT
(e) BTB
(f) (3C - 2E)TB (g) AT(D + F) (h) BTC + A (i) (2E)AT (j) (BT + A)C.
5. Determine a constant k such that (kA)T(kA) = 1, where
1 1 2
A .
For no. 6 – 7, given
3 2
5 4 , 1 2 3
4 1 0
5 4 2 ,
4 2
2 -3 ,
3 1 2
5 1 4
3 1 -3 ,
2 3
1 2
0 1 ,
4 1 2
3 2 1
F E
D C
B A
If possible compute :
(a). AT and (AT)T (c). (2D + 3F)T (e). 2AT + B (b). (C + E)T and CT + ET (d). D - DT (f). (3D - 2F)T If possible compute :
(a). (2A)T (c). (3BT - 2A)T (e). (A)Tand(A)T (b). (A - B)T (d). (3AT - 5BT)T (f). (C + E + FT)T
Types of Matrices A. Identity Matrix Example 15:
1. Upper Triangular Matrix
3 0 0 0
2 -0 0 0
2 1 3 0
1 1 2 -1 , 3 0 0
1 2 -0
3 -2 1 , 1 0
2 1
C B
2. Lower Triangular Matrix
3. Diagonal Matrix
4. Scalar Matrix
5. Identity Matrix
B. Square Matrices Example 16:
1. If and
B are called commutative matrices.
2. If
0 0 and
, 3. A is a periodic matrix with period 2, because
maka
4. A and B are idempotent matrices, cause
5. A is called nilpotent matrix with index 2, because
if A A O
6. A and B are called involuntary matrices, because
if then 2 3
C. Hermitian Matrix Example 17: Given
and
because B B
i
3. iB is a Hermitian Matrix, because
iB
. and
,
5. B is a skew Hermitian matrix, because
B
and ,
YOGYAKARTA STATE UNIVERSITY
MATHEMATICS AND NATURAL SCIENCES FACULTY MATHEMATICS EDUCATION STUDY PROGRAM Topic: Augmented Matrix
An arbitrary system of m linear equations in n unknowns can be written as,
This system can be abbreviated by writing in matrix term
With A is a coefisien matrix and
is called an augmented
Example 18: The augmented matrix for the system of 3 linear equations and 3 unknowns
. 3 2 2 3
7 4 3 2
5 2
z y x
z y x
z x
With
2 2 3
4 3 2
1 0 2
A ,
z y x
x , and
3 7 5
b , is
3 2 2 3
7 4 3 2
5 1 0 2
.
Example 19: The Matrix
5 2 0 3
4 3 1 2
is an augmented matrix of linear system
. 5 2 3
4 3 2
z x
z y x
Exercises 3:
1. Let see a linear system
. 5 3
3 4
3 2
2 3
2 3
7 2
z x
z y x
z y x
w x
(a) Find the coefisien matrix. (b) Find the augmented matrix. (c) Write the system on matrix term.
2. Write the linear system of this augmented matrix :
6 3 1 0 3
4 2 0 0 1
3 8 7 2 3
5 4 0 1 2
.
3. Write the linear system of this augmented matrix :
1 4 3 1
5 2 1 0
3 4 0 2
.
. 4 4
7 3
2 2
4 2 3
z x
z y
y x
z y
x
(a) Find the coefisien matrix. (b) Find the augmented matrix. (c) Write the linear system on matrix term.
5. Find the answer with elimination methods
8 2
9 3
y x
y x
. 6. Find the answer (if any) of this linear system
5 13 4 2
2 2
z y x
z y x
z y x
.
7. Find a and b, so this linear system has
(i). exactly one solution (ii). no solution (iii). Infinitely many solution
(a).
5 1 2 by ax
y x
(b).
5 2
1 y ax
by x
(c).
3 1 ay x
by x
. 8. Given the linear system
r fy ex
q dy cx
p by ax
When the lines of the 3 linear eqution makes (i). the system has exactly one solution, (ii). the system has no solution,
(iii). the system has infinitely many solution.
9. For number 8, if the equation systems consistent, then one of the equations can be eliminated without changing the solution set.
c z y x
b z x
a z y x
3 2
2
Suppose the system is consistent then a, b, and c has satisfy cab. 11.Prove: If the linear system x1kx2 candx1lx2 d has the same solution