Chapter 2 – Key Concepts Flashcards
Let A, B, and C be matrices of the same size, and let r and s be scalars. Evaluate the following w/ matrix algebra rules:
a. A + B
b. (A + B) + C
c. A + 0
d. r(A + B)
e. (r + s)A
f. r(sA)
a. A + B = B + A
b. (A + B) + C = A + (B + C)
c. A + 0 = 0
d. r(A + B) = rA + rB
e. (r + s)A = rA + sA
f. r(sA) = (rs)A
If A is m×n and B is n×p with B consisting of the columns [b1 … bp] then what is the product AB?
AB is the m×p matrix whose columns are given by [Ab1 … Abp]. That is, A [b1 … bp] = [Ab1 … Abp].
Each column of AB is a linear combination of what?
Every column of AB is a linear combination of the columns of A with weights given by the corresponding column of B.
What is the row-column rule for computing AB?
The element of AB in the ith column and jth row is given by:
(AB)ij = ai1b1j + … + ainbnj
What is the relationship between the ith row of AB and the ith row of A?
rowi(AB) = rowi(A) B
Let A be m×n and B and C have sizes that allow for the given multiplication to be defined. Then evaluate the following:
a. A(BC)
b. A(B + C)
c. (B + C)A
d. r(AB) for r ∈ ℝ
e. ImA and AIn
a. A(BC) = (AB)C
b. A(B + C) = AB + AC
c. (B + C)A = BA + CA
d. r(AB) = (rA)B = A(rB)
e. ImA = AIn = A
Evaluate the following in terms of matrix algebra:
a. AB vs BA
b. AB = AC vs. B = C
c. AB = 0 vs. A or B = 0
In general…
a. AB ≠ BA
b. AB = AC does not mean B = C
c. AB = 0 does not mean A = 0 or B = 0.
Evaluate: Ak for k ∈ ℝ.
Ak = A … A (k times)
Evaluate the following:
a. (AT)T
b. (A + B)T
c. (rA)T
d. (AB)T
a. (AT)T = A
b. (A + B)T = AT + BT
c. (rA)T = r(AT)
d. (AB)T = BTAT
The transpose of a product of matrices is what?
The product of the transposes in reverse order.
What does it mean for A to have an inverse A-1?
There exists some matrix such that:
AA-1 = A-1A = I
Say A = [[a b], [c d] ]. If ad-bc ≠ 0, what is A-1?
What if ad-bc = 0?
A-1 = (1 / (ad-bc)) [[d -b], [-c a] ]
If ad-bc = 0, then A is not invertible.
What is the determinant of a 2×2 matrix A?
If A = [[a b], [c d] ], then det(A) = ad-bc
If A is an n×n invertible matrix, then what must be true about the equation Ax = b for each b ∈ ℝn?
The equation Ax = b has the unique solution x = A-1b for all b ∈ ℝn.
Evaluate the following:
a. (A-1)-1
b. (AB)-1
c. (AT)-1
a. (A-1)-1 = A
b. (AB)-1 = B-1A-1
c. (AT)-1 = (A-1)T
What is the inverse of the product of n×n matrices?
The product of the inverses of each matrix in reverse order.
If an elementary row operation is performed on an m×n matrix A, how can we write the resulting matrix as a product of two matrices?
The resulting matrix is EA, where E is the m×m matrix created by performing the same row operation on Im.
Are all elementary matrices E invertible? If E does have an inverse, what is it?
Yes, their inverse is an elementary matrix of the same time that transforms E back into I.
If an n×n matrix A is invertible, what must be true about its relationship to In in terms of row equivalence? If A is row equivalent to In, then how can we get A-1 through elementary row operations?
A is row equivalent to In. The sequence of row operations that reduces A to In also transforms In into A-1.
Given A, how can A-1 be found or determined not to exist with row operations on an augmented matrix?
Row reduce [A I]. If A is row equivalent to I, then [A I] is row equivalent to [I A-1]. Otherwise, A does not have an inverse.
What is the invertible matrix theorem?
Say A is a square n×n matrix. The following are equivalent statements (all true or all false):
a. A is invertible.
b. A ~ In.
c. A has n pivot positions.
d. Ax = 0 has only the trivial solution.
e. The columns of A form an L.I. set.
f. x ↦ Ax is one-to-one.
g. Ax = b has at least 1 soln. ∀ b ∈ ℝn.
h. Columns of A span ℝn.
i. x ↦ Ax maps ℝn onto ℝn.
j. ∃ n×n C s.t. CA = I.
k. ∃ n×n D s.t. AD = I.
l. AT is invertible.
If A and B are square invertible, what must be true about the relationships between A, A-1, B, and B-1 if AB = I?
B = A-1 and A = B-1.
Let T : ℝn → ℝn and the std matrix of T be A. If T is invertible, what must be true about A? What is the inverse of T equal to?
A must be invertible.
The inverse of T is S s.t. S(x) = A-1x and T and S satisfy the following:
- S(T(x)) = x ∀ x ∈ ℝn.
- T(S(x)) = x ∀ x ∈ ℝn.
If A is m×n and B is n×p, what is the column-row expansion of AB?
AB = [col1(A) … coln(A)] [row1(B) … rown(B)] = col1(A)row1(B) + … + coln(A)rown(B)
What does it mean for H to be a subspace of ℝn?
H must have the following three properties:
a. 0 ∈ H.
b. ∀ u, v ∈ H, u + v ∈ H.
c. ∀ u ∈ H and c ∈ ℝ, cu ∈ H.
What is the column space of a matrix A?
The column space of a matrix A is the set Col A of all linear combinations of the columns of A.
What is the null space of a matrix A?
The null space of a matrix A is the set Nul A of all solutions of the homogeneous equation Ax = 0.
The null space of an m×n matrix A is a subspace of what? Equivalently, the solution set of Ax = 0 is a subspace of what?
ℝn
What is a basis for a subspace?
A basis for a subspace H of ℝn is a linearly independent set in H that spans H.
What components of A form a basis for the column space of A?
The pivot columns of A.
Let B = {b1, …, bp} be a basis for a subspace H. For a given x ∈ H, what are the coordinates of x relative to the basis B? What is the B-coordinate vector of x?
The coordinates of x relative to the basis B are the weights c1, …, cp s.t. x = c1b1 + … + cpbp.
The B-coordinate vector of x is: [x]B = [c1 … cp].
What is the dimension of a subspace?
The dimension of a nonzero subspace H, denoted by dim H, is the number of vectors in any basis for H. The dimension of the zero subspace {0} is defined to be zero.
What is the rank of a matrix?
The rank of a matrix A, denoted by rank A, is the dimension of the column space of A.
What does the rank theorem say?
If a matrix A has n columns, then rank A + dim Nul A = n
What does the basis theorem say?
Let H be a p-dimensional subspace of ℝn. Any linearly independent set of exactly p elements in H is automatically a basis for H. Also, any set of p elements of H that spans H is automatically a basis for H.
What does the continued invertible matrix theorem say?
Let A be n×n invertible, then the following are equivalent (all true or all false) along with the rest of the IMT:
n. The columns of A form a basis of ℝn
m. Col A = ℝn
o. dim Col A = n
p. rank A = n
q. Nul A = {0}
r. dim Nul A = 0