final matrix ppt

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Matrix ..types addition subtraction multiplication inverse

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Algebra

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0011 0010 1010 1101 0001 0100 1011

DEFINATION

A matrix is a collection of numbers arranged into a fixed number of rows

and columns.

A

a11 ,, a1n

a21 ,, a2n

am1 ,, amn

Aij

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0011 0010 1010 1101 0001 0100 1011

TYPES

VECTOR MATRIX

SCALAR MATRIX

SQUARE MATRIX

SYMMETRIC MATRIX

DIAGONAL MATRIX

IDENTITY MATRIX

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0011 0010 1010 1101 0001 0100 1011

VECTOR MATRIX

A vector is a special type of matrix that has only one row (called a row vector) or one column (column vector ) .Below A is a column while B is a row vector.

3

1

4

A 1 7 4 5 B

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0011 0010 1010 1101 0001 0100 1011

SCALAR MATRIX

A diagonal matrix in which all of the diagonal elements are equal is called Scalar Matrix 

5 0 0

0 5 0

0 0 5

B

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0011 0010 1010 1101 0001 0100 1011

SQUARE MATRIX

3 1 2

1 6 3

7 4 5

A

A matrix with same number of rows and columns is a square matrix

5 3

4 7 B

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0011 0010 1010 1101 0001 0100 1011

SYMMETRIC MATRIX

A symmetric matrix is square matrix in which = for all i and j matrix A is symmetric matrix.

OR, A=A'

4251 3

0011 0010 1010 1101 0001 0100 1011

DIAGONAL MATRIX

A diagonal matrix is a matrix is a symmetric matrix where all the off diagonal elements are 0 .

Ex:-

5 0 0

0 5 0

0 0 5

B

4251 3

0011 0010 1010 1101 0001 0100 1011

IDENTITY MATRIX

An identity matrix is a diagonal matrix with 1 & only 1 on diagonal .The diagonal matrix is always denoted as I

1 0 0

0 1 0

0 0 1

A

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0011 0010 1010 1101 0001 0100 1011

Addition

Subtraction

Multiplication

Inverse

Matrix Operations

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0011 0010 1010 1101 0001 0100 1011

Two matrices can be added or subtracted if and only if the number of rows and columns are same.

ADDITION AND SUBTRACTION

4251 3

0011 0010 1010 1101 0001 0100 1011A

a11 a12

a21 a22

B b11 b12

b21 b22

22222121

12121111

baba

babaBA

If and

then

22222121

12121111

baba

babaBA

also

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0011 0010 1010 1101 0001 0100 1011

EXAMPLE

1

4

2

3

5

8

6

7+ =

6

12

8

10

A B+ = C

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0011 0010 1010 1101 0001 0100 1011

EXAMPLE

1

4

2

3

5

8

6

7- =

4

4

4

4

B A- = C

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0011 0010 1010 1101 0001 0100 1011

Multiplication Matrices A and B can be multiplied if the no. of coloum of first matrix is same as the no. of rows of the second

[r x c] and [s x d]

c = s

i.e.

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0011 0010 1010 1101 0001 0100 1011

Step I

1

4

2

3

5

8

6

7x =

A Bx =

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0011 0010 1010 1101 0001 0100 1011

Step II

1

4

2

3

5

8

6

7x =

A Bx = C

(5x1)

C 11 = A 11 x B 11k=1

n

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0011 0010 1010 1101 0001 0100 1011

Step III

1

4

2

3

5

8

6

7x =

A Bx = C

(5x1)+ (6x3)

C 11 = A 12 x B 21k=2

n

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0011 0010 1010 1101 0001 0100 1011

Step IV

1

4

2

3

5

8

6

7x =

A Bx = C

23 (5x2)+ (6x4)

C 12 = A 1k x B k2k=1

n

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0011 0010 1010 1101 0001 0100 1011

Step V

1

4

2

3

5

8

6

7x =

A Bx = C

23

(7x1)+ (8x3)

34

C 21 = A 2k x B k1k=1

n

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0011 0010 1010 1101 0001 0100 1011

Step VI

1

4

2

3

5

8

6

7x =

A Bx = C

23 34

(7x2)+ (8x4)31

C 22 = A 2k x B k2k=1

n

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0011 0010 1010 1101 0001 0100 1011

Result

1

4

2

3

5

8

6

7x =

A Bx = C

23 34

31 46

m x n n x p m x p

Inverse

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0011 0010 1010 1101 0001 0100 1011

Find determinant

Swap the diagonal

elements(a11 and a22)

Change signs of non-

diagonal elements(a12

and a21)

Divide each element by determinant

INVERSE OF A 2x2 MATRIX

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0011 0010 1010 1101 0001 0100 1011

Step I--Find the determinant

A determinant is a scalar number which is calculated from a matrix. This number can determine whether a set of linear equations are solvable, in other words whether the matrix can be inverted.

• Find the determinant = (a11 x a22) - (a21 x a12)

For

det(A) = (2x3) – (1x5) = 1

2

3

5

1=A

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0011 0010 1010 1101 0001 0100 1011

Step II--Swap elements a11 and a22

• Swap elements a11 and a22

Thus

becomes

2

3

5

1=A

3

2

5

1

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0011 0010 1010 1101 0001 0100 1011

Step III--Change sign of a12 and a21

• Change sign of a12 and a21

Thus

becomes

3

2

5

1=A

3

2

-5

-1

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0011 0010 1010 1101 0001 0100 1011

Step IV

• Divide every element by the determinantThus

becomes

(no change as the determinant was 1)

3

2

-5

-1=A

3

2

-5

-1

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0011 0010 1010 1101 0001 0100 1011

Step V– Check the result

• Check results with A-1 A = IThus

equals

3

2

-5

-1x

1

1

0

0

2

3

5

1

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