Math 415 Exam 2 Solutions: Inner Products, Orthogonality, and Linear Systems, Exams of Linear Algebra

Solutions to exam 2 of math 415, which covers topics such as inner products, orthonormal bases, and linear systems. It includes demonstrations of why the integral definition of an inner product on f([-1, 1]) fails, finding the a = ldlt factorization of a matrix, and determining the closest point in a plane to a vector. It also covers fredholm's criterion and compatibility conditions for linear systems.

Typology: Exams

Pre 2010

Uploaded on 03/11/2009

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Math 415 Exam # 2 Solutions
1. (10 points)
(a) Demonstrate why
hf, g i=Z1
1
f(x)g(x)xdx
is not an inner product on F([1,1]).
Solution: (5 points) Show that positivity fails. Take f(x) = 1, for example.
Then
k1k2=h1,1i=Z1
1
1·1·xdx =1
2x2|1
1= 0
but f(x) = 1 is not the zero vector.
(b) Find a weighted inner product hv,wi=av1w1+bv2w2+cv3w3for which
the vectors v=1 2 1Tand w=01 3 Tare orthogonal.
Solution: (5 points) The inner product of the two vectors is hv,wi=
a·1·0 + b·2·(1) + c·(1) ·3 = 2b3c. For this to be zero, b
and cwould have to be of opposite signs. But for a,b, and cto define a
weighted inner product, they all need to be positive. So this problem has
no solution.
2. (15 points)
(a) Find the A=LDLTfactorization of
A=
1 2 1
260
1 0 9
Solution: (6 points) By Gaussian-elimination
1 2 1
260
1 0 9
1 2 1
0 2 2
0 2 8
1 2 1
0 2 2
0 0 6
and so
D=
100
020
006
and L=
1 0 0
2 1 0
111
(b) Given that
K=
9 45 54
45 223 256
54 256 233
=
100
510
671
900
02 0
007
156
017
001
1
pf3
pf4

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Math 415 Exam # 2 Solutions

  1. (10 points)

(a) Demonstrate why

〈f, g〉 =

− 1

f (x)g(x)xdx

is not an inner product on F([− 1 , 1]).

Solution: (5 points) Show that positivity fails. Take f (x) = 1, for example.

Then

2 = 〈 1 , 1 〉 =

− 1

1 · 1 · xdx =

x

2 |

1 − 1 = 0

but f (x) = 1 is not the zero vector.

(b) Find a weighted inner product 〈v, w〉 = av 1 w 1 + bv 2 w 2 + cv 3 w 3 for which

the vectors v =

)T

and w =

)T

are orthogonal.

Solution: (5 points) The inner product of the two vectors is 〈v, w〉 =

a · 1 · 0 + b · 2 · (−1) + c · (−1) · 3 = − 2 b − 3 c. For this to be zero, b

and c would have to be of opposite signs. But for a, b, and c to define a

weighted inner product, they all need to be positive. So this problem has

no solution.

  1. (15 points)

(a) Find the A = LDL

T factorization of

A =

Solution: (6 points) By Gaussian-elimination

and so

D =

 (^) and L =

(b) Given that

K =

write the quadratic form q(x) = x

T Kx as a sum of squares of expressions

in x. Is q(x) positive definite, negative definite, or indefinite, and why?

Solution: (9 points) Set

y = L

T x =

x 1

x 2

x 3

x 1 + 5x 2 + 6x 3

x 2 + 7x 3

x 3

Then q(x) = x

T Kx = y

T Dy = 9y

2 1 −^2 y

2 2 + 7y

2 3 = 9(x^1 + 5x^2 + 6x^3 )

2 −

2(x 2 + 7x 3 )

2

  • 7x

2 3.^ We see that^ q(x) is indefinite because the diagonal

elements of D are not all positive and not all negative.

  1. (10 points)

(a) Define what is meant by an orthonormal basis. Give an example of one in

R

2 relative to the dot product that does NOT contain either of the stan-

dard basis vectors.

Solution: (5 points) An orthonormal basis is a basis that is mutually or-

thogonal and in which all vectors are unit vectors. An example is

v 1 =

, v 2 =

(b) Give a proof that if v 1 , v 2 , and v 3 are mutually orthogonal, then they are

linearly independent.

Solution: (5 points) If

c 1 v 1 + c 2 v 2 + c 3 v 3 = 0

then taking inner products of both sides with v 1 gives us

0 = c 1 v 1 · v 1 + c 2 v 2 · v 1 + c 3 v 3 · v 1 = c 1 ||v 1 ||

2

  • c 2 0 + c 3 0 = c 1 ||v 1 ||

2

Since v 1 is none-zero, we see that c 1 = 0. In the same way you can show

that c 2 and c 3 are zero.

  1. (10 points) Using distance measured by the dot product, find the point in the

plane W spanned by v 1 and v 2 closest to the vector v where

v 1 =

 (^) , v 2 =

 (^) , v =

What is the distance between W and v?

Solution: You can either switch to an orthogonal basis and do an orthogonal

projection or write down and solve the normal equations.

Method 1: Set

w 1 = v 1 =

 (^) , w 2 =^ v 2 −^

v 2 · w 1

||w 1 ||^2

w 1 =

1 2 1 1 2

is connected. Thus the kernel of A

T is the vector of all 1’s, and so the

compatibility condition is

b 1

b 2

b 3

b 4

b 5

= b 1 + b 2 + b 3 + b 4 + b 5

(c) One solution of the system below is x =

)T

. What

equations should be added to the system to find the unique solution of

minimum norm?.

          1 − 1 0 0 0

1 0 − 1 0 0

x 1

x 2

x 3

x 4

x 5

Solution: (3 points) The coefficient matrix here is the incident matrix for a

connected digraph, so its kernel is spanned by the vector of all ones. Thus,

to find the solution of minimum norm we must add the equation

x 1

x 2

x 3

x 4

x 5

= x 1 + x 2 + x 3 + x 4 + x 5