(a)
is norm :
(1)
(2)
that is
(3)
(4)
If
hence norm 1 is norm .
(b)
(1)
Take c in R,
(2)
.
(3)
(4)
If
hence infinite norm is norm.
Q5 (a) Provide the definition of the derivative of a map F: ViV2 where (V, l1) a are normed vector spaces (possibly infinite dimensional) (b) Let C((0, 1) be the space of continuous real valued functions on [0, 1] endowed with the supremum norm. Define F:C ((0, 1]) C([0, 1]) by F(() Jo f()dt, e for all f E C(0, 1). Show directly from the definition that the derivative of F is differentiable on the entire domain. (c) For the...
Let V and W be finite dimensional vector spaces over R and T:V + W be linear. Let V be a subspace of V and Wo = T(V). (Select ALL that are TRUE) If T is surjective then Vo = {v EV : there is w E Wo such that T(v) = w} If T is injective then dim(VO) = dim(W). dim(ker(T) n Vo) = dim(VO) - dim(Wo).
Problem 13.5. Let V and W be inner product spaces and T є L(V : W). Let(..) v and (..)w denote their respective mner products. Let ui, , uk be an orthonormal basts o V and W1,…,wn an orthonormal bass o W. Let A and A* be the matrices representing T and T with respect to the given bases. Show that A. = A i.e., A. is obtained from A by taking the transpose and conjugating all the entries (in...
Let U,V,W be vector spaces over field F, and let S ∈ L(U,V) andT ∈ L(V,W). (a) Show that if T ◦ S is injective, then S is injective (b) Give an example showing that if T ◦ S is injective then T need not be injective. (c) Show that if T ◦ S is surjective, then T is surjective. (d) Give an example showing that if T ◦ S is injective then S need not be surjective.
Let V and W be a vector spaces over F and T ∈ L(V, W) be invertible. Prove that T-1 is also linear map from W to V . Please show all steps, thank you
Let V and W be two vector spaces over R and T:V + W be a linear transformation. We call a linear map S: W → V a generalized inverse of T if To SOT = T and SoTo S = S. If T is an isomorphism, show that T-1 is the unique generalized inverse of T.
Let V and W be two vector spaces over R and T:V + W be a linear transformation. We call a linear map S:W → V a generalized inverse of T if To SoT=T and SoToS = S. If V and W are finite dimensional, show that there exists a generalized inverse of T.
Let (V,〈 , 〉v) and (W.〈 , 〉w) be finite-dimensional inner product spaces. Recall that the adjoint L* : W → V of a linear function L Hom(V,W) is completely determined by the equation <L(v), w/w,-(v, L* (w)של for every v є V and w є W . Use this to prove the following facts: (a) (Li + L2)* = Lİ + L: for Li, L26 Horn(V,W) (b) (α L)* =aL' for a R and L€ Horn(V,W) (c) (L*)* =...
Let V and W be two vector spaces over R and T:V + W be a linear transformation. We call a linear map S: W → V a generalized inverse of T if To SOT = T and SoTo S = S. If V and W are finite dimensional, show that there exists a generalized inverse of T.
Problem 13 (10 pts) If L :V + W is a linear transformation of vector spaces and U CW is a subspace of W, then {v EV | L(v EU} CW is a subspace of V.