Any Method - Linear Algebra - Solved Exam, Exams of Linear Algebra

This is the Solved Exam of Linear Algebra which includes Empty, Unique Solution, Contains, Equation, Solution, Calculations, Possible, Solution, Set, Three Vectors etc. Key important points are: Any Method, Angle, System, Vectors, Symmetric Matrix, Diagonal Matrix, Satisfies, Equation, Functions, Rotation Matrix

Typology: Exams

2012/2013

Uploaded on 02/27/2013

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Answer Key for Exam #1
1. The vectors
1
3
5
1
and
2
2
2
2
have lengths 6 and 4, respectively:
p12+ 32+ (5)2+ 12=36 = 6 and p22+ (2)2+ 22+ 22=16 = 4.
Their dot product is 1·2+3(2)+(5)2+1·2 = 12, so the angle θbetween them satisfies cos θ=12
6·4=1
2.
Therefore θ= 120, or θ=2π
3.
2. We use elimination on an augmented matrix. First two steps: subtract three times the first row from the
second, and four times the first row from the third. Next two steps: multiply the second row by 1, and
then add twice the new second row to the third. This gives
1 5 6 22
3 4 1 3
42 5 37
1 5 6 22
011 17 63
022 19 51
1 5 6 22
0 11 17 63
0 0 15 75
.
The third equation gives x3= 5. Then the second equation becomes 11x2+ 85 = 63, so x2=2. Finally
the first equation becomes x110 + 30 = 22, so x1= 2.
3(a) Step 1: subtract three times the first row of Afrom the second row, and subtract the first row from the
third. Step 2: subtract twice the second row from the third.
A=
1 2 1
3 7 6
1 4 8
1 2 1
0 1 3
0 2 7
1 2 1
0 1 3
0 0 1
=U.
Step 1 puts 3 in the second row, first column of L; and 1 in the third row, first column. Then step 2 puts a
2 in the second row, third column of L, so L=
100
310
121
.
3(b) We may now solve A~x =
5
8
12
in two steps. First we solve L~y =~
b, which in this case is
1 0 0
3 1 0
1 2 1
y1
y2
y3
=
5
8
12
and we get y1= 5; 15 + y2= 8, so y2=7; and 5 14 + y3=12, so y3=3. Finally we solve U ~x =~y,
which in this case is
1 2 1
0 1 3
0 0 1
x1
x2
x3
=
5
7
3
.
Here we have x3=3; x29 = 7, so x2= 2; x1+ 4 3 = 5, so x1= 4.
3(c) Here we have to reduce [L I] to £I L1¤by row operations, which is not too hard:
100 100
310 010
121 001
100 100
010 3 1 0
021 1 0 1
1 0 0 1 0 0
0 1 0 3 1 0
0 0 1 5 2 1
.
pf3
pf4

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Answer Key for Exam #

  1. The vectors

 and

 have lengths 6 and 4, respectively:

12 + 3^2 + (−5)^2 + 1^2 =

36 = 6 and

22 + (−2)^2 + 2^2 + 2^2 =

Their dot product is 1·2+3(−2)+(−5)2+1·2 = −12, so the angle θ between them satisfies cos θ =

Therefore θ = 120◦, or θ = 23 π.

  1. We use elimination on an augmented matrix. First two steps: subtract three times the first row from the second, and four times the first row from the third. Next two steps: multiply the second row by −1, and then add twice the new second row to the third. This gives

 

The third equation gives x 3 = 5. Then the second equation becomes 11x 2 + 85 = 63, so x 2 = −2. Finally the first equation becomes x 1 − 10 + 30 = 22, so x 1 = 2.

3(a) Step 1: subtract three times the first row of A from the second row, and subtract the first row from the third. Step 2: subtract twice the second row from the third.

A =

 = U.

Step 1 puts 3 in the second row, first column of L; and 1 in the third row, first column. Then step 2 puts a

2 in the second row, third column of L, so L =

3(b) We may now solve A~x =

 (^) in two steps. First we solve L~y = ~b, which in this case is

y 1 y 2 y 3

and we get y 1 = 5; 15 + y 2 = 8, so y 2 = −7; and 5 − 14 + y 3 = −12, so y 3 = −3. Finally we solve U~x = ~y, which in this case is (^) 

x 1 x 2 x 3

Here we have x 3 = −3; x 2 − 9 = −7, so x 2 = 2; x 1 + 4 − 3 = 5, so x 1 = 4.

3(c) Here we have to reduce [L I] to

[

I L−^1

]

by row operations, which is not too hard:  

So L−^1 =

. From this it is a reasonable guess that U −^1 =

, since U is a

sort of “double transpose” of L and this is what we get by transposing L−^1 across both diagonals. One can easily check that (^) 

 = I,

so this must indeed be U −^1. Alternatively we can reduce [U I] to

[

I U −^1

]

by row operations:  

3(d) Since A = LU and L and U are both invertible, we have A−^1 = U −^1 L−^1. Therefore

A−^1 =

4(a) Step 1: subtract twice the first row of A from the second row, three times the first row from the third row, and 4 times the first row from the fourth row. Step 2: subtract twice the second row from the fourth.

A =

 =^ U.

Step 1 puts 2, 3 , 4 respectively in the second through fourth rows of column 1 of L, and step 2 puts a 2 in

the second row, fourth column of L, so L =

 and^ A^ =^ LU^.

4(b) Since A is symmetric, we should be able to rewrite U = DLT^ where D is a diagonal matrix containing the pivots of A. Factoring 1, − 2 , − 6 , −4 respectively from the rows of U we have

D =

 and the remaining matrix is

 = LT^.

4(c) To find D−^1 we simply invert each number on the diagonal of D:

D−^1 =

 =^

To find L−^1 we have to reduce [L I] to

[

I L−^1

]

by row operations, which is not too hard:   

So problems 5 and 6 taken together have derived the 2 × 2 inverse formula.

  1. A reflection matrix R satisfies R^2 = I, so the Cayley-Hamilton theorem holds with u = 0 and v = 1. A projection matrix P satisfies P 2 = P , so the Cayley-Hamilton theorem holds with u = 1 and v = 0. The square of a rotation matrix is not particularly interesting. If

T =

cos θ − sin θ sin θ cos θ

rotates counterclockwise by θ, then T 2 rotates counterclockwise by 2θ. The trace of T is cos θ +cos θ = 2 cos θ and the determinant of T is 1, so u = 2 cos θ and v = −1 and we have T 2 = (2 cos θ) T − I, or in other words

( cos 2θ − sin 2θ sin 2θ cos 2θ

= (2 cos θ)

cos θ − sin θ sin θ cos θ

The trigonometric identities that this implies are cos 2θ = 2 cos^2 θ − 1 and sin 2θ = 2 sin θ cos θ.

Scores: The median was 93, and the mean was 91.625.

Score Frequency Score Frequency Score Frequency 100 1 95 2 88 1 99 1 94 1 87 2 98 2 93 3 86 1 97 2 92 1 84 1 96 2 90 2 67 1