Eigen Values and Eigen Vectors Flashcards

1
Q

Equation used for eigen vector and eigen values

A

AX = λX

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Give basic definition of eigen vector and eigen values

A

Let Aₙₓₙ for any scalar λ, ∃ X≠0 (non-zero vector) such that AX = λX
λ is called eigen value of Anxn
and
X ≠ 0 is called eigen vector corresponding to λ.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Another name of Eigen value

A

Characteristic value of Aₙₓₙ

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

AX = λX
explain it in words

A

Matrix multiplication of vector = Scalar multiple of vector

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Characteristic equation

A

|A - λI|=0

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

How to find eigen values

A

By solving characteristic equation i.e |A - λI|=0

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

How to find Eigen vectors

A

By solving (A - λI)X = 0. {here X≠0}

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

No. of Independent eigen vectors

(formula not definition)

A

No. of independent eigen vectors for an eigen value λ = n - rank(A-λI) = no. of free variable of A-λI
=geometric multiplicity of λ

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

General characteristic equation of A

A

|A-λI| = (-1)ⁿ λⁿ + (-1)ⁿ⁻¹ Trace(A) λⁿ⁻¹ + ——-+|Anxn| = 0

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Aₙₓₙ has _______________ number of eigen values

A

Anxn has n number of eigen values

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Note of General characteristic equation

A

If coefficient of λⁿ is (-1)ⁿ then constant term of characteristic polynomial of Aₙₓₙ = |A| = determinant of A
and
coefficient of λⁿ⁻¹ = (-1)ⁿ⁻¹ Trace(A)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

How do we get determinant of matrix by general characteristic equation

A

If coefficient of λⁿ is (-1)ⁿ then the constant term = determinant of matrix

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

How do we get Trace(A) by characteristic equation

A

If coefficient of λⁿ is (-1)ⁿ then
(-1)ⁿ⁻¹ Trace(A) = coefficient of λⁿ⁻¹

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Sum of eigen values of matrix A

A

Trace(A)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Trace(A) in terms of eigen values

A

Trace(A) = Sum of eigen values of A

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Product of eigen values

A

Determinant of matrix
i.e.|A|

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

Determinant of A in terms of eigen values

A

Product of eigen values

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

A and Aᵀ
explain in context of eigen values

A

eigen values of A = eigen values of Aᵀ

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

If |A| = 0 then
explain in context of eigen values

A

If |A| = 0 then at least one eigen value = 0

20
Q

If |A|≠ 0
explain in context of eigen values

A

If |A|≠ 0 then none of the eigen value is 0

21
Q

Eigen values of symmetric matrix

A

Real

22
Q

Eigen values of skew-symmetric matrix

A

zero or purely imaginary

23
Q

Eigen values of orthogonal matrix

A

|λ| = 1
i.e. Eigen values of orthogonal matrix are of unit modulus (|λ| = 1)

24
Q

Eigen values of unitary matrix

A

|λ| = 1
i.e. Eigen values of unitary matrix are of unit modulus (|λ| = 1)

25
Q

Rank of A
in context of eigen values

A

Number of non-zero eigen values

26
Q

If λ is eigen value of A. Then
eigen value of Aᵏ __________

A

Eigen value of Aᵏ is λᵏ

27
Q

If λ is eigen value of A. Then
eigen value of kA ___________

A

Eigen value of kA is kλ

28
Q

If λ is eigen value of A. The eigen value of aₙ Aⁿ +aₙ₋₁ Aⁿ⁻¹+——+ a₁A + a₀I is

A

Eigen value of aₙ Aⁿ +aₙ₋₁ Aⁿ⁻¹+——+ a₁A + a₀I is
aₙ λⁿ +aₙ₋₁ λⁿ⁻¹+——+ a₁λ+a₀

29
Q

Special about A, A², ……, Aᵏ ,A⁻¹, kA, adj A, polynomial matrix in A, eᴬ

A

Eigen vectors of A, A², ……, Aᵏ ,A⁻¹, kA, adj A, polynomial matrix in A, eᴬ are same

30
Q

If λ is eigen value of ______________ then
1.) _________ is eigen value of A⁻¹
2.) _________ is eigen value of (adj A)

A

If λ is eigen value of non-singular matrix then
1.) 1/λ is eigen value of A⁻¹
2.) |A|/λ is eigen value of (adj A)

31
Q

Eigen vectors of ____________________ are same

A

Eigen vectors of A, A², ……, Aᵏ ,A⁻¹, kA, adj A, polynomial matrix in A, eᴬ are same

32
Q

Eigen values of Involuntary matrix

A

are ±1

33
Q

Eigen values of Idempotent matrix

A

are 0,1

34
Q

Eigen values of Lower Triangular matrix, Upper Triangular matrix

A

are principal diagonal elements

35
Q

Eigen values of Diagonal matrix

A

are principal diagonal elements

36
Q

Definition of eigen value in terms of matrix

A

Every matrix can be replaced by its eigen value

37
Q

Number of eigen values

A

Number of eigen values = Order of matrix i.e. n

38
Q

Eigen values of Nilpotent Matrix

A

Eigen values of Nilpotent matrix are zero

39
Q

If one eigen value of real matrix is complex then what about its other eigen value

A

The eigen values of real matrix must occur in complex conjugate pair if any of the eigen values are complex

40
Q

Absolute value of the product eigen values

A

Absolute value of the product eigen values = absolute value of determinant of matrix
|λ₁ λ₂ λ₃ ……… λₙ | = |det(A)|

41
Q

Eigen values of Identity matrix of order nxn

A

The eigenvalues of an identity matrix I of order nxn are all** 1**
In other words, the eigenvalues of Iₙ are 1,1,1,….,1(repeated n times)

42
Q

Eigen values of AAᵀ

A

Eigen values of AAᵀ are always greater or equal to zero. i.e. λ(AAᵀ) ≥ 0

43
Q

Eigen Values of AAᵀ are real or not
give reason also

A

eigen values of AAᵀ are always real because AAᵀ is symmetric matrix

44
Q

Eigen values of AdjA if λ is eigen value of Non-singular matrix

A
45
Q

Non-zero eigenvalues of AAᵀ is

A

Number of non-zero eigen values of AAᵀ is equal to rank A
since [rank A = rank of AAᵀ]

46
Q

Compare the geometric and algebraic multiplicity of λ

A

Geometric multiplicity of λ ≤ Algebraic multiplicity of λ
i.e. The geometric of an eigen value λ of a Matrix A doesn’t exceed its algebraic multiplicity

47
Q
A