Linear Algebra Primatives Flashcards

(57 cards)

1
Q

If matrix A has an inverse, then

A
  • the inverse is unique
  • A-1A=I
  • AA-1=I
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2
Q

(A-1)-1=

A

A

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3
Q

if A and B are non-singular matricies, then (inverse relations)

A

(AB)-1=B-1A-1

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4
Q

If A is non-singular and k ne 0, then (inverses)

A

(kA)-1=(1/k)A-1

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5
Q

If A and B are matrices such that AB is defined (ie conformable), then (transposes)

A

(AB)T=BTAT

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6
Q

A is called symmetric if

A

AT=A

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7
Q

If A and B are nxn square matrices, then (determinants)

A

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

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8
Q

If A in nxn, then det(A) = 0 IFF

A

A is singular

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9
Q

The rank of A is

A

the greatest number of linearly independent columns (or rows) of A

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10
Q

If A and B are non-singular, then for any matrix C, (ranks)

A

C, AC, CB, ACB all have the same rank (assuming multiplications defined)

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11
Q

If A in an mxn matrix of rank r, then there exists non-singular matrices P and Q such that PAQ equals one of the following:

A
  • I (this is “eye”)
  • [I 0]
  • [I 0]T
  • [I 0 0 0] (square)
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12
Q

The rank of AB can not exceed

A

the rank of either the rank of A or B

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13
Q

If A is a nxn matrix, then det(A)=0 IFF (rank)

A

the rank of A is less than n

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14
Q

The matrix of a quadratic form can always be chosen to be

A

symmetric (attach proof)

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15
Q

A and B are said to be congruent matrices IFF

A

there exists a non-singular matrix, C, such that B=CTAC.

We say C is the congruent transformation of A.

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16
Q

Let A be an nxn symmetric of rank r. There exists a non-singular matrix C such that

A

CTAC = D where

D is a diagonal matrix with exactly r non-zero diagonal elements

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17
Q

If A and B are congruent matricies, then

A

they have the same rank

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18
Q

Let C be an mxn matrix with rank r, then the ranks of CTC and CCT are

A

also r.

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19
Q

Let A be an nxn matrix. There always exist n complex numbers …

A

eigenvalues (characteristic roots, symbol lambda) that satisfy

det(A-lambda I) = 0. If A is real symmetric, then all lambda’s are real.

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20
Q

Let A be an nxn symmetric matrix, the rank of A (in terms of eigenvalues)

A

is the number of non-zero eigenvalues

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21
Q

Let A be an nxn matrix. A has ____ eigenvalues IFF A is singular.

A

A has at least one zero eigenvalue.

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22
Q

Let A be an nxn matrix. The determinant of A (in terms of eigenvalues)

A

the product of its eigenvalues

Π lambdai

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23
Q

Let A be an nxn matrix, and let C be any nxn non-singular matrix. The following matrices all have the same eigenvalues

A
  • A
  • C-1AC
  • CAC-1
24
Q

Let A be an nxn real matrix. A necessary and sufficient condition that there exists a nonzero y that satisfies:

Ay=lambda * y

A

is that lambda be an eigenvalue of A.

25
Let P be an nxn matrix. P is called orthonormal IFF
P-1=P' THUS P'P=I
26
P'P=I suggests
P is orthonormal
27
Let A be an nxn matrix, and let P be an orthonormal matrix, then (determinants)
det(A) = det(P'AP)
28
Let x and y be nx1 vectors. x and y are called orthogonal if
x'y = 0
29
Let A be an mxn matrix and B be a nxp matrix. And and B are said to be orthoganal to each other IF
AB=0
30
Let A ben an nxn symmetric matrix. There exists an orthonormal matrix P such that
P'AP = D where Di is a diagonal matrix whose diagonal elements are the eigenvalues of A.
31
Full rank factorization. Let A be an mxn matrix with rank r\>0. There exists matrices AL (mxr with rank r) and AR (rxn with rank r) such that:
A=ALAR
32
The column space of a matrix A is :
the set of vectors that can be generated as linear combinations of columns of A. (ditto for rowspace).
33
Let A be an nxn matrix. A is called positive semidefinite if:
* A=A' (symtric) * y'Ay ge 0 for all y * There exists at least one y ne 0 such that y'Ay=0.
34
If A is positive semidefinite, then
* Rank of A is less than n * The eigenvalues of A are greater than or equal to 0 * Let P be a nxn non-singular matrix. P'AP is also p.s.d.
35
Let A be an nxn matrix. A is called positive definite if
* A=A' * y'Ay\>0 for all y ne 0
36
If A is positive definite, then
* The rank of A is n * All the eigenvalues of A are greater than 0 * Let P be a nxn non-singular matrix. P'AP is also positive definite
37
A matrix is called non-negative definite if
it is either positive definite or positive semi-definite
38
Let C be an mxn matrix with rank r. C'C and CC' are both
non-negative definite. They are positive definite IFF they have full rank.
39
Let A be a nxn symmetric non-negative definite matrix. There exists some nxn matrix B such that
B'B=A
40
Let A and B be nxn symmetrix matrices. If A is positive definite, then there exists a non-singular matrix Q, such that
* Q'AQ=I and * Q'BQ=D where D is a diagonal matrix whose diagonal elements are roots of det(B-lambda A) = 0
41
If A and B are both non-negative dfinite, then there exists a matrix Q such that both Q'AQ and Q'BQ are both
diagonal
42
43
Consider a matrix of the attached form. It can be shown that the inverse of this matrix is:
44
Let A be an nxn matrix. A is idempotent if
AA=A
45
If A is an nxn idempotent matrix with rank n, then
A=I
46
If A is an nxn idempotent matrix of rank less than n, then A is
positive semidefinite
47
If A is an nxn idempotent matrix with rank r, then it has ___ non-zero eigenvalues each equal to \_\_\_.
r non-zero eigenvalues each equal to 1
48
Let A ben an nxn (symmetric) idempotent matrix. * A' is * Let P be an orthonormal matrix. P'AP is * Let P be an nxn non-singular matrrix. PAP-1 is * I - A is
* A' is (symetric) idempotent * Let P be an orthonormal matrix. P'AP is (symmetric) idempotent * Let P be an nxn non-singular matrrix. PAP-1 is idempotent * I - A is (symmetric) idempotent
49
Trace A
Σ diagonal elements
50
Let A be mxn and B be an nxm matrix. Trace(AB) =
trace(BA)
51
trace(ABC)
trace(CAB)
52
Let A be an nxn matrix and P be a non-singlular nxn matrix trace(A) =
trace(P-1AP)
53
Let A be an nxn matrix and P be a orthonormal nxn matrix trace(A) =
trace(A) = trace(P'AP)
54
Let A be an nxn matrix with eigenvalues lambda 1, ... n trace(A) =
sum of eigenvalues
55
If A is an idempotent matrix, then trace(A) =
trace(A) = rank(A)
56
Let A and B be nxn matrices, and let a and b be scalars. trace(aA + bB) =
trace(aA + bB) = a\*trace(A) + b\*trace(B)
57
Let A be an nxn matrix trace(A) =
trace(A) = trace(A')