Sample Midterm Problems and Solutions for Math 201B, Winter 2007, Exams of Mathematical Methods for Numerical Analysis and Optimization

Sample midterm problems and brief solutions for math 201b, a course on functional analysis, offered in winter 2007. The problems cover various topics such as measurable subsets, orthogonal projections, fubini's theorem, fourier coefficients, and stability of sets in a hilbert space.

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Pre 2010

Uploaded on 07/30/2009

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Sample Midterm Problems
Brief Solutions
Math 201B, Winter 2007
Problem 1. Let ERbe a measurable subset of R. Define a linear
subspace Mof L2(R) by
M=fL2(R)|f(x) = 0 a.e. in E.
Find M. What is the orthogonal projection of fL2(R) onto M?
Solution.
Let Ec=R\Ebe the complement of E. Then
M=fL2(R)|f(x) = 0 a.e. in Ec.
The direct-sum decomposition of fis
f=χEcf+χEf,
where χEis the characteristic function of E, and χEcfis the orthogonal
projection of fonto M.
Problem 2. Let
E=(x, y)R2|0< x < ,0< y < 1.
Prove that ZE
ysin xexy dxdy =1
2log 2.
Solution.
To apply Fubini’s theorem, first check that
ZEysin xexydxdy ZE
yexy dxdy
=Z1
0Z
0
yexy dxdy
<.
pf3
pf4
pf5

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Sample Midterm Problems

Brief Solutions

Math 201B, Winter 2007

Problem 1. Let E ⊂ R be a measurable subset of R. Define a linear

subspace M of L

2 (R) by

M =

f ∈ L

2 (R) | f (x) = 0 a.e. in E

Find M

. What is the orthogonal projection of f ∈ L

2 (R) onto M?

Solution.

  • Let E

c = R \ E be the complement of E. Then

M

f ∈ L

2 (R) | f (x) = 0 a.e. in E

c

  • The direct-sum decomposition of f is

f = χEc f + χE f,

where χE is the characteristic function of E, and χEc f is the orthogonal

projection of f onto M.

Problem 2. Let

E =

(x, y) ∈ R

2 | 0 < x < ∞, 0 < y < 1

Prove that (^) ∫

E

y sin xe

−xy dxdy =

log 2.

Solution.

  • To apply Fubini’s theorem, first check that

E

∣y sin xe−xy

∣ (^) dxdy ≤

E

ye

−xy dxdy

0

0

ye

−xy dx

dy

  • Then compute the iterated integral

0

0

y sin xe

−xy dx

dy.

Problem 3. Let T, S ∈ L

2 (T) be the triangular and square waves, defined

respectively by

T (x) = |x| if |x| < π, S(x) =

1 if 0 < x < π,

− 1 if −π < x ≤ 0,

Compute the Fourier coefficients of T , S. Show that T ∈ H

1 (T) and T

′ = S.

Show that S /∈ H

1 (T).

Solution.

  • From the definition of the Fourier coefficient,

fˆ n =^

2 π

∫ (^) π

−π

f (x)e

−inx dx,

we compute that

n =

π

[

n − 1

n^2

]

n 6 = 0, Tˆ 0 =

π

2

√ 2 π

S^ ˆ

n =^ i

π

[

n − 1

n

]

n 6 = 0, Sˆ 0 = 0.

  • The sum ∑

n∈Z

n

2

n

2

converges, since

1 /n

2 converges, so T ∈ H

1 (T). Since Sˆn = in Tˆn,

we have S = T

′ .

  • The series ∑

n∈Z

n

2

n

2

does not converge, since the terms do not approach zero as n → ∞, so

S /∈ H

1 (T).

Problem 5. An indexed set of vectors {uα | α ∈ A} in a Hilbert space H is

said to be stable if there exist constants m, M > 0 such that for all

{cα | cα ∈ C, α ∈ A} ∈ `

2 (A)

we have

m

α∈A

|cα|

2 ≤

α∈A

cαuα

2

≤ M

α∈A

|cα|

2 .

(a) Show that a stable set is linearly independent, and an orthonormal set is

stable.

(b) Suppose that {uα | α ∈ A} is a set of normalized vectors (‖uα‖ = 1) such

that (^) ∑

α 6 =β

|〈uα, uβ 〉|

2 < 1.

Show that {uα | α ∈ A} is stable.

(c) Let {en | n ∈ Z} be an orthonormal set, and define

un =

en + en+ √ 2

Show that {un | n ∈ Z} is not stable.

Solution.

  • (a) If {uα | α ∈ A} is stable and

α∈A

cαuα = 0,

then ∑

α∈A

|cα|

2 = 0.

Hence cα = 0 for all α ∈ A, so a stable set is linearly independent. (In

fact, what we have shown is stronger than linear independence, since

we did not consider only finite linear combinations of the vectors.)

  • For an orthonormal set ∥ ∥ ∥ ∥ ∥

α∈A

cαuα

2

α∈A

|cα|

2

so the set is stable, with m = M = 1.

  • (b) We have ∥ ∥ ∥ ∥ ∥

α∈A

cαuα

2

α,β∈A

cαcβ 〈uα, uβ 〉.

Using the Cauchy-Schwarz inequality, we get

α,β∈A

cαcβ 〈uα, uβ 〉 =

α∈A

|cα|

2

α 6 =β

cαcβ 〈uα, uβ 〉

α∈A

|cα|

2

α 6 =β

|cαcβ |

2

α 6 =β

|〈uα, uβ 〉|

2

α∈A

|cα|

2

α∈A

|cα|

2

α 6 =β

|〈uα, uβ 〉|

2

α∈A

|cα|

2 ,

and

α,β∈A

cαcβ 〈uα, uβ 〉 =

α∈A

|cα|

2

α 6 =β

cαcβ 〈uα, uβ 〉

α∈A

|cα|

2 −

α 6 =β

|cαcβ |

2

α 6 =β

|〈uα, uβ 〉|

2

α 6 =β

|〈uα, uβ 〉|

2

α∈A

|cα|

2 .

  • (c) Consider, for example, cn = (−1)

n for 1 ≤ n ≤ N and cn = 0

otherwise. Then (^) ∑

n∈Z

|cn|

2 = N,

and (^) ∥ ∥ ∥ ∥ ∥

n∈Z

cnun

2

N eN +1 − e 1 √ 2

2

Since N ∈ N is arbitrary, there is no constant m > 0 with the required

property for stability.