- Problem 1: Affine functions. A function f : Rn β Rm is said to be affine if for any x, y βRn and any Ξ±, Ξ²βR with Ξ± + Ξ² = 1, we have
f(Ξ±x + Ξ²y) = Ξ±f(x) + Ξ²f(y).
Note that without the restriction Ξ± + Ξ² = 1, this would be the definition of linearity.
- Suppose that A βRmΓn and b βRm. Show that the function f(x) = Ax + b is affine.
- Prove the converse, namely, show that any affine function f can be represented uniquely as f(x) = Ax + b for some A βRmΓn and b βRm.
- Problem 2: Linear Maps and Differentiation of polynomials. Let Pn be the vector space consisting of all polynomials of degree β€ n with real coefficients. (a) Consider the transformation T : Pn βPn defined by
dp(x)
T(p(x)) =Β Β .
dx
For example, T(1 + 3x + x2) = 3 + 2x. Show that T is linear.
(b) Using {1, x, . . . , xn} as a basis, represent the transformation in part (a) by a matrix A βR(n+1)Γ(n+1). Find the rank of A.
- Problem 3: Matrix Rank Inequalities.
Show the following identities about rank. (a) If A βFmΓn,B βFnΓk then
rank(B) β€ rank(AB) + dim(null(A))
- If A βFmΓn,B βFmΓn then
rank(A + B) β€ rank(A) + rank(B)
- Suppose A, B βFmΓm. Then show that if AB = 0 then
rank(A) + rank(B) β€ m
- Suppose A βFmΓm. Then show A2 = A if and only if
rank(A) + rank(A β I) = m
where I βFmΓm is the identity matrix.
- Problem 4: Solution of Linear System of Equations. Consider the system of linear equations
y = ABx
where A βRnΓn and B βRnΓm, m β€ n. For each of the following cases, find conditions (in terms of null spaces and range spaces of A and B) under which there can be a unique solution, no solution, or infinite number of solutions.
- rank(A) = n, and rank(B) = m.
- rank(A) = n, and rank(B) < m. (c) rank(A) < n, and rank(B) = m.
- Problem 5: Infinite Dimensional Vector Spaces. Recall that C0([0,1]) is defined as the set of all continuous functions f : [0,1] β R, is a vector space over R. Let S = {1, (x + 1), (x + 2)2, (x + 3)3, . . . , (x + i)i, . . . }.
- Is there a vector in S which can be represented as a finite linear combination of other vectors in S?
- Can any vector in C0([0,1]) be represented as a finite linear combination of vectors in S?
[Finite linear combination is a linear combination with finite number of terms]



