Problem 1
1.1 If A is an n x n matrix, prove that if A has n linearly
independent eigenvalues, then AT is diagonalizable.
1.2 Diagonalize the matrix below with eigenvalues equal to -1
and 5.
0
1
1
2
1
2
3
3
2
1.3 Assume that A is 4 x 4 and has three different eigenvalues,
if one of the eigenspaces is dimension 1 while the other is
dimension 2, can A be undiagonalizable? Explain.
Answer for all...
1. For an m x n matrix A, the Column Space of A is a subspace of
what vector space?
2. For an m x n matrix A, the Null Space of A is a subspace of
what vector space?
Let A be an m x n matrix. Prove that
Ax = b has at least one solution
for any b if and only if A has linearly
independent rows.
Let V be a vector space with dimension 3, and let
V = span(u, v,
w). Prove that u,
v, w are linearly independent (in
other words, you are being asked to show that u,
v, w form a basis for
V)
A m*n matrix A. P is the dimension of null space of A. What are
the number of solutions to Ax=b in these cases. Prove your
answer.
a. m=6, n=8, p=2
b. m=6, n=10, p=5
c. m=8, n=6, p=0
1. Prove that the Cantor set contains no intervals.
2. Prove: If x is an element of the Cantor set, then there is a
sequence Xn of elements from the Cantor set converging
to x.