Determinants - Computer Sciences - Lecture Slides, Slides of Operating Systems

These lecture slides are very easy to understand the computer operating system.The major points in these lecture slides are:Determinants, Main Results, Main Properties of Determinants, True, Adjust Signs, Individually, Each Column, Definition, Swapped, Permutation

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2012/2013

Uploaded on 04/25/2013

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DETERMINANTS CHAP. 3
Determinants: summary of main results
äWe begin with the determinant of a 2×2matrix
det "a b
c d #=ad bc
Notation : det (A)or
a b
c d
äNext we list the main properties of determinants.
äProperties also true for n×ncase. In fact they motivate
the definition of det (A)for n > 2.
äDet. of an n×nmatrix = product of pivots when
permutation is not used. Adjust signs when permuting.
I-2
äProperties written for columns (easier to write) but are
also true for rows
Notation: We let A= [u, v]columns u, and vare in R2.
1If v=αu then det (A) = 0.
äDeterminant of linearly dependent vectors is zero
äIf any one column is zero then determinant is zero
2Interchanging columns or rows:
det [v, u] = det [u, v]
3Linearity:
det [u, αv +βw] = αdet [u, v] + βdet [u, w]
I-3
ädet (A)= linear function of each column (individually)
ädet (A)= linear function of each row (individually)
-What is the determinant det [u, v +αu]?
4Determinant of transpose
det (A) = det (AT)
5Determinant of Identity
det (I)= 1
6Determinant of a diagonal:
det (D)=d1d2···dn
I-4
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DETERMINANTS CHAP. 3

Determinants: summary of main results

ä We begin with the determinant of a 2 × 2 matrix

det

[

a b

c d

]

= ad − bc

Notation : det (A) or

a b

c d

ä Next we list the main properties of determinants.

ä Properties also true for n×n case. In fact they motivate

the definition of det (A) for n > 2.

ä Det. of an n × n matrix = product of pivots when

permutation is not used. Adjust signs when permuting.

I-

ä Properties written for columns (easier to write) but are

also true for rows

Notation: We let A = [u, v] columns u, and v are in R 2 .

1 If v = αu then det (A) = 0.

ä Determinant of linearly dependent vectors is zero

ä If any one column is zero then determinant is zero

2 Interchanging columns or rows:

det [v, u] = −det [u, v]

3 Linearity:

det [u, αv + βw] = αdet [u, v] + βdet [u, w]

ä det (A) = linear function of each column (individually)

ä det (A) = linear function of each row (individually)

  • What is the determinant det [u, v + αu]?

4 Determinant of transpose

det (A) = det (A T )

5 Determinant of Identity

det (I) = 1

6 Determinant of a diagonal:

det (D) = d 1 d 2 · · · dn

7 Determinant of a triangular matrix (upper or lower)

det (T ) = a 11 a 22 · · · ann

8 Determinant of product of matrices [IMPORTANT]

det (AB) = det (A)det (B)

9 Consequence: Determinant of inverse

det (A

− 1 ) =

1 det (A)

  • What is the determinant of αA?
  • What can you say about the determinant of a matrix

which satisfies A 2 = I?

  • Is it true that det (A + B) = det (A) + det (B)?

I-

Determinants – general definition

ä Consider now the general situation of n × n matrices:

A =

a 11 a 12 · · · a 1 n

a 21 a 22 · · · a 2 n .. .

an 1 an 2 · · · ann

General idea: det of A is the sum of all possible products

of one entry per row of A. Each product has a sign.

ä Consider the situation n = 3.

ä We will need to use all permutations of [1, 2 , 3]

ä σ = [2, 1 , 3] is one such permutation. Its signature is

− 1 because we need one interchange to go from [1, 2 , 3]

to [2, 1 , 3] (swapped 1 and 2)

I-

ä σ = [3, 1 , 2] is another such permutation. It signature

is +1 because we need two interchanges to go from [1, 2 , 3]

to [3, 1 , 2]

ä Here are all permutations with their signatures

σ Sign.

[ 1 2 3 ] +

[ 1 3 2 ] − 1

[ 2 3 1 ] +

[ 2 1 3 ] − 1

[ 3 1 2 ] +

[ 3 2 1 ] − 1

ä We will denote by sig(σ) the signature of σ

Definition of Det.

det (A) =

σ

sig(σ)a 1 σ(1)a 2 σ(2) · · · anσ(n)

Where the sum runs over all (n!) possible permutations

of [1, 2 , , · · · , n].

Case n = 3 σ Sign. Det =

[ 1 2 3 ] +1 +a 11 a 22 a 33

[ 1 3 2 ] − 1 −a 11 a 23 a 32

[ 2 3 1 ] +1 +a 12 a 23 a 31

[ 2 1 3 ] − 1 −a 12 a 21 a 33

[ 3 1 2 ] +1 +a 13 a 21 a 32

[ 3 2 1 ] − 1 −a 13 a 22 a 31