Diagonalization, Quadratic forms Flashcards

1
Q

Explain Diagonalization

A
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2
Q

In diagonalization, which transformation used?

A

Similarity transformation
Aₙₓₙ can be diagonalised using similarity transformation B=P⁻¹AP where P is non-singular matrix

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3
Q

In P⁻¹AP = D
What is P here

A

P is non-singular matrix which is given by P = [X₁ X₂ X₃ …….Xₙ]ₙₓₙ consisting of all n independent eigen vectors of Aₙₓₙ
P is called Modal matrix

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4
Q

Explain similarity transformation

A

P⁻¹AP = B
Here A and B are similar matrices i.e. eigen values of A and B are same

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5
Q

P⁻¹AP = B
Tell us about A and B here

A

Here A and B are similar matrices i.e.
eigen values of A and B are same

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6
Q

Necessary and sufficient condition for Aₙₓₙ to get diagonalised

A

no. of independent eigen vectors of Aₙₓₙ = order of Aₙₓₙ = n

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7
Q

D =P⁻¹AP
what is D here

A
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8
Q

If A and D are similar matrices what about their determinants

A

|A|=|D|

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9
Q

________________ is also very important in getting diagonalized matrix

A

Order of eigen values is also very important in getting diagonalized matrix

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10
Q

Explain Dⁿ if D is given

A

If D = P⁻¹AP then Dⁿ = P⁻¹AⁿP

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11
Q

Explain A if D is given

A

If D = P⁻¹AP then A = PDP⁻¹

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12
Q

Explain Aⁿ if A is given

A

If A = PDP⁻¹ then Aⁿ = PDⁿP⁻¹

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13
Q

Explain eᴰ if D is given

A

If D = P⁻¹AP then eᴰ = P⁻¹eᴬP

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14
Q

Explain eᴬ if D is given

A

If D = P⁻¹AP then eᴬ = PeᴰP⁻¹

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15
Q

State transition matrix

A

If D = P⁻¹AP then eᴬ = PeᴰP⁻¹
here eᴬ is transition matrix

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16
Q

Explain Quadratic Form

A
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17
Q

What type of matrix is in Quadratic From

A

Real symmetric matrix

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18
Q

Quadratic Form only definition

A

Xₙₓ₁ vector and Aₙₓₙ is a real symmetric matrix then XᵀAX is called quadratic form

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19
Q

Equation of Quadratic form

20
Q

Special type of quadratic form

A

Orthogonal Form

21
Q

Another names of orthogonal form (2)

A

Canonical Form or Sum of squares of quadratic form

22
Q

Explain orthogonal form

23
Q

Orthogonal form of quadratic form (only definition)

A

It is given by YᵀDY where Y = [Y₁Y₂….Yₙ]ᵀ, Y∈Rⁿ

24
Q

Equation of orthogonal form

A

Orthogonal form of quadratic form: λ₁Y₁²+ λ₂Y₂²+ λ₃Y₃²+ …..+ λₙYₙ²

25
Nature of quadratic form (5)
1.) If XᵀAX > 0 ∀ X∈Rⁿ OR λ>0, then Q.F. is positive definite 2.) If XᵀAX ≥ 0 ∀ X∈Rⁿ OR λ≥0, then Q.F. is semi positive definite 3.) If XᵀAX < 0 ∀ X∈Rⁿ OR λ<0, then Q.F. is negative definite 4.) If XᵀAX ≤ 0 ∀ X∈Rⁿ OR λ≤0, then Q.F. is semi negative definite 5.) If XᵀAX>0 and ≤ 0 ∀ X∈Rⁿ OR λ>0 and ≤0, then Q.F. is indefinite (Here λ is eigen value of A)
26
Condition for finding nature of quadratic form
In XᵀAX, X≠0
27
Q.F. is positive definite
XᵀAX > 0 ∀ X∈Rⁿ OR λ>0
28
Q.F. is semi positive definite
XᵀAX ≥ 0 ∀ X∈Rⁿ OR λ≥0
29
Q.F. is negative definite
XᵀAX < 0 ∀ X∈Rⁿ OR λ<0
30
Q.F. is semi-negative definite
XᵀAX ≤ 0 ∀ X∈Rⁿ OR λ≤0
31
Q.F is indefinite
If XᵀAX>0 and ≤ 0 ∀ X∈Rⁿ OR λ>0 and ≤0
32
XᵀAX > 0 ∀ X∈Rⁿ Tell the nature of Q.F
Q.F. is positive definite
33
λ>0 Tell the nature of Q.F.
Q.F. is positive definite
34
XᵀAX ≥ 0 ∀ X∈Rⁿ Tell the nature of Q.F.
Q.F. is semi positive definite
35
λ≥0 Tell the nature of Q.F.
Q.F. is semi positive definite
36
XᵀAX < 0 ∀ X∈Rⁿ Tell the nature of Q.F.
Q.F. is negative definite
37
λ<0 Tell the nature of Q.F.
Q.F. is negative definite
38
XᵀAX ≤ 0 ∀ X∈Rⁿ Tell the nature of Q.F.
Q.F. is semi-negative definite
39
λ≤0 Tell the nature of Q.F.
Q.F. is semi-negative definite
40
If XᵀAX>0 and ≤ 0 ∀ X∈Rⁿ Tell the nature of Q.F.
Q.F is indefinite
41
λ>0 and ≤0 Tell the nature of Q.F.
Q.F is indefinite
42
Rank of Quadratic form
Rank of Q.F. = Rank of A = no. of non-zero eigen values of A = r
43
How to denote Index of Q.F
p
44
Index of Q.F
p = number of positive eigen values of A
45
What is Signature of Q.F.
excess +ve compared to -ve λ of A
46
Formula of signature of Q.F.
2p - r Here p is index of Q.F. and r is rank of Q.F.