

Study with the several resources on Docsity
Earn points by helping other students or get them with a premium plan
Prepare for your exams
Study with the several resources on Docsity
Earn points to download
Earn points by helping other students or get them with a premium plan
The solutions to exercises 5, 10, and 22 from section 3.5 and section 3.6, and exercises 3, 8, and 16 from section 4.1 in math 415. The solutions cover topics such as matrix transformations, linear independence, column spaces, and linear operators.
Typology: Assignments
1 / 2
This page cannot be seen from the preview
Don't miss anything!


Math 415 HW #6 Sol’n page 1of 2
Section3.5 Exercise5: a) The transition matrix from [e 1 , e 2 , e 3 ] to [u 1 , u 2 , u 3 ] is
− 1
=
b) The coordinates wrt [u 1 , u 2 , u 3 ] are:
i) A(3, 2 , 5)T^ = (1, − 4 , 3)T^ ; ii) A(1, 1 , 2)T^ = (0, − 1 , 1)T^ ; iii) A(3, 3 , 2)T^ = (2, 2 , −1)T^.
Section3.6 Exercise10: Recall that dimension of row space equals to the dimension of column space and that row equivalent matrices have the same rank, we have rank of A = rank of U = 2. Also notice that a 1 and a 2 are linear independent, hence a 3 and a 4 are linear combinations of a 1 and a 2. Thus we can write a 3 = xa 1 + ya 2 , a 4 = za 1 + wa 2 for some x, y, z, w ∈ R:
− 3 4 − 3 x + 4y − 3 z + 4w 5 − 3 5 x − 3 y 5 z − 3 w 2 7 2 x + 7y 2 z + 7w 1 − 1 x − y z − w
Now since A and U are row equivalent, they have the same row space. Thus (− 3 , 4 , − 3 x+ 4 y, − 3 z+4w), (5, − 3 , 5 x− 3 y, 5 z− 3 w) are linear combinations of (1, 0 , 2 , 1) and (0, 1 , 1 , 4). We have (− 3 , 4 , − 3 x + 4y, − 3 z + 4w) = a(1, 0 , 2 , 1) + b(0, 1 , 1 , 4) and (5, − 3 , 5 x − 3 y, 5 z − 3 w) = c(1, 0 , 2 , 1) + d(0, 1 , 1 , 4) for some a, b, c, d ∈ R. Comparing the first two coordi- nates in these two equations, we see immediately that a = − 3 , b = 4, c = 5, d = −3. Substituting them back and looking the rest two coordinates, we have
− 3 x + 4y = 2 · (−3) + 1 · ( − 3 z + 4w = 1 · (−3) + 4 · (4) 5 x − 3 y = 2 · (5) + 1 · (−3) 5 z − 3 w = 1 · (5) + 4 · (−3).
Solving these equations, we have x = 2, y = 1, z = 1, w = 4. Therefore a 3 = (− 2 , 7 , 11 , 1)T^ and a 4 = (13, − 7 , 30 , −3)T^.
Section3.6 Exercise22: a)To show the column space of C = AB is a subspace of the column space of A, it suffices to show that each column vector of C is a linear combination of column vectors of A. Now let bi be the i − th column vector of B. Then we know the i − th column vector of C = AB is Abi. (See textbook page 38). Now we write A = (a 1 , ..., an) where
Math 415 HW #6 Sol’n page 2of 2
each ai is a column vector. And write down bi = (bi 1 , ..., bin)T^ explicitly. In this way, we have Abi = bi 1 a 1 + ... + binan which is a linear combination of column vectors of A. Thus we proved a. b) We can prove this in two ways. First we can prove it similar to a). Or we can apply a) to CT^ = BT^ AT^. The fact that column space of one matrix is the row space of its transpose gives us a second proof. c) By a) Column rank of C ≤ Column rank of A. By b) Row rank of C ≤ Row rank of B. In fact we know that rank= column rank =row rank. Thus rank(C) ≤ min{rank(A), rank(B)}.
Section4.1 Exercise3: We have L( 0 ) = a, which is a given nonzero vector. Hence L can not be a linear trans- formation.
Section4.1 Exercise8: a) Yes: L(aA + B) = C(aA + B) + (aA + B)C = aCA + CB + aAC + BC = a(CA + AC) + (CB + BC) = aL(A) + L(B). b) Yes: Similar computation. c) No, in general: If L were a linear operator, then we have 0 = L(I + (−I)) = L(I) + L(−I) = I^2 C + (−I)^2 C = 2C, which isn’t always true. If fact, L is a linear operator if and only if C = 0, the zero matrix.
Section4.1 Exercise16: Let’s verify:
L(au 1 + u 2 ) = L 2 (L 1 (au 1 + u 2 )) becauseL = L 2 (L 1 ) = L 2 (aL 1 (u 1 ) + L 1 (u 2 )) because L 1 is a linear operator = aL 2 (L 1 (u 1 )) + L 2 (L 1 (u 2 )) because L 2 is a linear operator = aL(u 1 ) + L(u 2 ) L = L 2 (L 1 ).
Thus L is a linear operator.