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HW2, Math 307. CSUF. Spring 2007

Nasser M. Abbasi

spring 2007   Compiled on October 14, 2025 at 5:15pm  [public]

Contents

1 Section 1.5, Problem 2
2 Section 1.5, Problem 5
3 Section 1.5, Problem 6
4 Section 1.5, Problem 9
5 Section 1.5, problem 24
6 Section 1.5, problem 42

1 Section 1.5, Problem 2

Problem: What multiple \(l_{32}\) of row 2 of \(A\) will elimination subtract from row 3 of \(A\)? Use the factored form \(A=\overset {L}{\overbrace {\begin {bmatrix} 1 & 0 & 0\\ 2 & 1 & 0\\ 1 & \fbox {4} & 1 \end {bmatrix} }}\overset {U}{\overbrace {\begin {bmatrix} 5 & 7 & 8\\ 0 & 2 & 3\\ 0 & 0 & 6 \end {bmatrix} }}\)what will be the pivots? will a row exchange be required?

Solution:

\(l_{32}=4\), hence elimination will subtract \(4\) times row \(2\) from row 3.

Looking at the \(U\) matrix, we see the pivots along the diagonal of the matrix: \(\begin {bmatrix} \fbox {$5$} & 7 & 8\\ 0 & \fbox {$2$} & 3\\ 0 & 0 & \fbox {$6$}\end {bmatrix} \)

To find out if a row exchange will be needed or not, first determine \(A\)

\[ A=\begin {bmatrix} 1 & 0 & 0\\ 2 & 1 & 0\\ 1 & 4 & 1 \end {bmatrix}\begin {bmatrix} 5 & 7 & 8\\ 0 & 2 & 3\\ 0 & 0 & 6 \end {bmatrix} =\allowbreak \begin {bmatrix} 5 & 7 & 8\\ 10 & 16 & 19\\ 5 & 15 & 26 \end {bmatrix} \]

Carry the first elimination, we get

\[ A=\allowbreak \begin {bmatrix} 5 & 7 & 8\\ 0 & 2 & 3\\ 0 & 8 & 18 \end {bmatrix} \]

Hence, there would not be a need for a row exchange.

2 Section 1.5, Problem 5

Problem: Factor \(A\) into \(LU\) and write down the upper triangular system \(Ux=c\) which appears after elimination for

\[ Ax=\begin {bmatrix} 2 & 3 & 3\\ 0 & 5 & 7\\ 6 & 9 & 8 \end {bmatrix}\begin {bmatrix} u\\ v\\ w \end {bmatrix} =\begin {bmatrix} 2\\ 2\\ 5 \end {bmatrix} \]

Answer:

\(A=\begin {bmatrix} \fbox {$2$} & 3 & 3\\ 0 & 5 & 7\\ 6 & 9 & 8 \end {bmatrix} \overset {l_{21}=0}{\Rightarrow }\begin {bmatrix} \fbox {$2$} & 3 & 3\\ 0 & 5 & 7\\ 6 & 9 & 8 \end {bmatrix} \overset {l_{31}=3}{\Rightarrow }\begin {bmatrix} 2 & 3 & 3\\ 0 & \fbox {$5$} & 7\\ 0 & 0 & -1 \end {bmatrix} \overset {l_{32}=0}{\Rightarrow }\begin {bmatrix} 2 & 3 & 3\\ 0 & 5 & 7\\ 0 & 0 & \fbox {$-1$}\end {bmatrix} \)

Hence

\begin{align*} L & =\begin {bmatrix} 1 & 0 & 0\\ l_{21} & 1 & 0\\ l_{31} & l_{32} & 1 \end {bmatrix} \\ & =\fbox {$\begin {bmatrix} 1 & 0 & 0\\ 0 & 1 & 0\\ 3 & 0 & 1 \end {bmatrix} $}\end{align*}

and

\[ U=\fbox {$\begin {bmatrix} 2 & 3 & 3\\ 0 & 5 & 7\\ 0 & 0 & -1 \end {bmatrix} $}\]

Hence now we can write \(Ax=b\) as \(\left ( LU\right ) x=b\), or \(L\left ( Ux\right ) =b\), Where \(Ux=c\)

We can solve for \(c\) by solving \(Lc=b\), then we solve for \(x\) by solving \(Ux=c\)

3 Section 1.5, Problem 6

Problem: Find \(E^{2}\) and \(E^{8}\) and \(E^{-1}\) if \(E=\begin {bmatrix} 1 & 0\\ 6 & 1 \end {bmatrix} \)

Answer:

\(E^{2}\left ( A\right ) \) means \(E\left ( E\left ( A\right ) \right ) \), which means we first subtract \(-6\) times first row from second row of \(A\), then apply \(E\) to this result again, subtracting \(-6\) times first row from the second row of the resulting matrix.  

Hence the net result is subtracting \(-12\) times first row from the second row of the original matrix \(A.\)

Hence in general, we write

\[ E^{n}=\begin {bmatrix} 1 & 0\\ n\times 6 & 1 \end {bmatrix} \]

Therefore

\begin{align*} E^{2} & =\begin {bmatrix} 1 & 0\\ 2\times 6 & 1 \end {bmatrix} =\begin {bmatrix} 1 & 0\\ 12 & 1 \end {bmatrix} \\ E^{8} & =\begin {bmatrix} 1 & 0\\ 8\times 6 & 1 \end {bmatrix} =\begin {bmatrix} 1 & 0\\ 48 & 1 \end {bmatrix} \\ E^{-1} & =\begin {bmatrix} 1 & 0\\ -1\times 6 & 1 \end {bmatrix} =\begin {bmatrix} 1 & 0\\ -6 & 1 \end {bmatrix} \end{align*}

4 Section 1.5, Problem 9

Problem: (a) Under what conditions is the following product non singular?

\[ A=\overset {L}{\overbrace {\begin {bmatrix} 1 & 0 & 0\\ -1 & 1 & 0\\ 0 & -1 & 1 \end {bmatrix} }}\overset {D}{\overbrace {\begin {bmatrix} d_{1} & 0 & 0\\ 0 & d_{2} & 0\\ 0 & 0 & d_{3}\end {bmatrix} }}\overset {V}{\overbrace {\begin {bmatrix} 1 & -1 & 0\\ 0 & 1 & -1\\ 0 & 0 & 1 \end {bmatrix} }}\]

(b) Solve the system \(Ax=b\) starting with \(Lc=b\)

\[ \overset {L}{\overbrace {\begin {bmatrix} 1 & 0 & 0\\ -1 & 1 & 0\\ 0 & -1 & 1 \end {bmatrix} }}\begin {bmatrix} c_{1}\\ c_{2}\\ c_{3}\end {bmatrix} =\begin {bmatrix} 0\\ 0\\ 1 \end {bmatrix} =b \]

Solution:

(a) Since \(U=\left [ D\right ] \left [ V\right ] =\begin {bmatrix} d_{1} & 0 & 0\\ 0 & d_{2} & 0\\ 0 & 0 & d_{3}\end {bmatrix}\begin {bmatrix} 1 & -1 & 0\\ 0 & 1 & -1\\ 0 & 0 & 1 \end {bmatrix} =\begin {bmatrix} d_{1} & -d_{1} & 0\\ 0 & d_{2} & -d2\\ 0 & 0 & d_{3}\end {bmatrix} \)

Hence the elements along the diagonal of \(U\) are the pivots. Then if any one of \(d_{1},d_{2},d_{3}\) is zero, then \(A\) will be non-singular

Hence for \(A\) to be non singular, then \(d_{1}\) and \(d_{2}\) and \(d_{3}\) must all be nonzero.

(b)

\begin{align*} Ax & =b\\ L\overset {c}{\overbrace {Ux}} & =b \end{align*}

\(Lc=b\) where \(Ux=c\)

hence starting with \(Lc=b\) we write

\[\begin {bmatrix} 1 & 0 & 0\\ -1 & 1 & 0\\ 0 & -1 & 1 \end {bmatrix}\begin {bmatrix} c_{1}\\ c_{2}\\ c_{3}\end {bmatrix} =\begin {bmatrix} 0\\ 0\\ 1 \end {bmatrix} \]

Solve for \(c\) by back substitution process \(\Rightarrow \) \(c_{1}=0\), \(c_{2}=0\), \(c_{3}=1\)

Hence now we write \(\left [ U\right ] x=c\) or

\[ \left [ D\right ] \left [ V\right ] x=c \]
\[ \overset {\left [ D\right ] \left [ V\right ] }{\overbrace {\begin {bmatrix} d_{1} & -d_{1} & 0\\ 0 & d_{2} & -d2\\ 0 & 0 & d_{3}\end {bmatrix} }}\begin {bmatrix} x_{1}\\ x_{2}\\ x_{3}\end {bmatrix} =\overset {c}{\overbrace {\begin {bmatrix} 0\\ 0\\ 1 \end {bmatrix} }}\]

Solve for \(x\) by back substitution process \(\Rightarrow \)

\[ x_{3}=\frac {1}{d_{3}}\]

and from second row, \(d_{2}x_{2}-d_{2}x_{3}=0\Rightarrow d_{2}x_{2}-\frac {d_{2}}{d_{3}}=0\), hence

\begin{align*} x_{2} & =\left ( \frac {d_{2}}{d_{3}}\right ) \frac {1}{d_{2}}\\ & =\frac {1}{d_{3}}\end{align*}

and from the first row, we have \(x_{1}d_{1}-x_{2}d_{1}=0\), hence \(x_{1}d_{1}=\frac {d_{1}}{d_{3}}\) \(\Rightarrow x_{1}=\frac {1}{d_{3}}\)

\[\begin {bmatrix} x_{1}\\ x_{2}\\ x_{3}\end {bmatrix} =\begin {bmatrix} \frac {1}{d_{3}}\\ \frac {1}{d_{3}}\\ \frac {1}{d_{3}}\end {bmatrix} \]

5 Section 1.5, problem 24

Problem: What three elimination matrices \(E_{21},E_{31},E_{32}\) put \(A\) into upper triangular form \(E_{32}E_{31}E_{21}A=U?\) Multiply by \(E_{32}^{-1},E_{31}^{-1},E_{21}^{-1}\) to factor \(A\) into \(LU\) where \(L=E_{21}^{-1}E_{31}^{-1}E_{32}^{-1}\). Find \(L\) and \(U\)

\[ A=\begin {bmatrix} 1 & 0 & 1\\ 2 & 2 & 2\\ 3 & 4 & 5 \end {bmatrix} \]

Solution:

\(\overset {A}{\overbrace {\begin {bmatrix} 1 & 0 & 1\\ 2 & 2 & 2\\ 3 & 4 & 5 \end {bmatrix} }}\overset {l_{21}=2}{\Rightarrow }\begin {bmatrix} 1 & 0 & 1\\ 0 & 2 & 0\\ 3 & 4 & 5 \end {bmatrix} \overset {l_{31}=3}{\Rightarrow }\begin {bmatrix} 1 & 0 & 1\\ 0 & 2 & 0\\ 0 & 4 & 2 \end {bmatrix} \overset {l_{32}=2}{\Rightarrow }\overset {U}{\overbrace {\begin {bmatrix} \fbox {$1$} & 0 & 1\\ 0 & \fbox {$2$} & 0\\ 0 & 0 & \fbox {$2$}\end {bmatrix} }}\)

Hence \(E_{21}=\begin {bmatrix} 1 & 0 & 0\\ -l_{21} & 1 & 0\\ 0 & 0 & 1 \end {bmatrix} ,E_{31}=\begin {bmatrix} 1 & 0 & 0\\ 0 & 1 & 0\\ -l_{31} & 0 & 1 \end {bmatrix} ,E_{32}=\begin {bmatrix} 1 & 0 & 0\\ 0 & 1 & 0\\ 0 & -l_{32} & 1 \end {bmatrix} \)

i.e. \(E_{21}=\begin {bmatrix} 1 & 0 & 0\\ -2 & 1 & 0\\ 0 & 0 & 1 \end {bmatrix} ,E_{31}=\begin {bmatrix} 1 & 0 & 0\\ 0 & 1 & 0\\ -3 & 0 & 1 \end {bmatrix} ,E_{32}=\begin {bmatrix} 1 & 0 & 0\\ 0 & 1 & 0\\ 0 & -2 & 1 \end {bmatrix} \)

\begin{align*} L & =E_{21}^{-1}E_{31}^{-1}E_{32}^{-1}=\overset {E_{21}^{-1}}{\overbrace {\begin {bmatrix} 1 & 0 & 0\\ 2 & 1 & 0\\ 0 & 0 & 1 \end {bmatrix} }}\overset {E_{31}^{-1}}{\overbrace {\begin {bmatrix} 1 & 0 & 0\\ 0 & 1 & 0\\ 3 & 0 & 1 \end {bmatrix} }}\overset {E_{32}^{-1}}{\overbrace {\begin {bmatrix} 1 & 0 & 0\\ 0 & 1 & 0\\ 0 & 2 & 1 \end {bmatrix} }}\\ & =\overset {E_{21}^{-1}}{\overbrace {\begin {bmatrix} 1 & 0 & 0\\ 2 & 1 & 0\\ 0 & 0 & 1 \end {bmatrix} }}\begin {bmatrix} 1 & 0 & 0\\ 0 & 1 & 0\\ 3 & 2 & 1 \end {bmatrix} \\ & =\overset {L}{\overbrace {\begin {bmatrix} 1 & 0 & 0\\ 2 & 1 & 0\\ 3 & 2 & 1 \end {bmatrix} }}\end{align*}

Hence \(L=\begin {bmatrix} 1 & 0 & 0\\ 2 & 1 & 0\\ 3 & 2 & 1 \end {bmatrix} ,U=\begin {bmatrix} 1 & 0 & 1\\ 0 & 2 & 0\\ 0 & 0 & 2 \end {bmatrix} \)

6 Section 1.5, problem 42

Problem: If \(P_{1}\) and \(P_{2}\) are permutation matrices, so is \(P_{1}P_{2}\). This still has the rows of \(I\) in some order. Give examples with \(P_{1}P_{2}\neq P_{2}P_{1}\), and examples of \(P_{3}P_{4}=P_{4}P_{3}\)

Solution:

A permutation matrix exchanges one row with another. It is used when the pivot is zero.

Assume \(P_{1}\) exchanges row \(i\) with row \(j.\) Assume \(P_{2}\) exchanges row \(k\) with row \(l.\) Hence \(P_{1}P_{2}\) exchanges row \(k\) with row \(l\) and next exchanges row \(i\) with row \(j\) of the resulting matrix.

For specific examples, Let \(P_{2}\) exchange second row with third row, and let \(P_{1}\) exchange second row with third row. Given \(A=\begin {bmatrix} R_{1}\\ R_{2}\\ R_{3}\end {bmatrix} \) hence \(P_{1}P_{2}\left ( A\right ) =P_{1}P_{2}\begin {bmatrix} R_{1}\\ R_{2}\\ R_{3}\end {bmatrix} =P_{1}\begin {bmatrix} R_{1}\\ R_{3}\\ R_{2}\end {bmatrix} =\begin {bmatrix} R_{3}\\ R_{1}\\ R_{2}\end {bmatrix} \)

While \(P_{2}P_{1}\left ( A\right ) =P_{2}P_{1}\begin {bmatrix} R_{1}\\ R_{2}\\ R_{3}\end {bmatrix} =P_{2}\begin {bmatrix} R_{2}\\ R_{1}\\ R_{3}\end {bmatrix} =\begin {bmatrix} R_{2}\\ R_{3}\\ R_{1}\end {bmatrix} \)

We see that the result is not the same. Hence in this example \(P_{1}P_{2}\neq P_{2}P_{1}\)

Now assume we have \(A=\begin {bmatrix} a\\ b\\ c\\ d \end {bmatrix} \), and let \(P_{3}\)be an exchange of the first and second rows, while \(P_{4}\) be an exchange of the third and 4th row. In this case we will see that \(P_{3}P_{4}=P_{4}P_{3}\)

Hence the rule is as follows

: If \(P_{1}\) exchanges row \(i\) with row \(j,\)and \(P_{2}\) exchanges row \(k\) with row \(l.\) Then \(P_{1}P_{2}=P_{2}P_{1}\) only when \(i,j,k,l\) are all not equal. (not counting the trivial case when \(i=j\), \(k=l\))

Specific examples

\(P_{1}=\begin {bmatrix} 0 & 0 & 1\\ 1 & 0 & 0\\ 0 & 0 & 1 \end {bmatrix} ,P_{2}=\begin {bmatrix} 1 & 0 & 0\\ 0 & 0 & 1\\ 0 & 1 & 0 \end {bmatrix} \Rightarrow P_{1}P_{2}=\begin {bmatrix} 0 & 1 & 0\\ 1 & 0 & 1\\ 0 & 1 & 0 \end {bmatrix} \neq P_{2}P_{1}=\begin {bmatrix} 0 & 0 & 1\\ 0 & 0 & 1\\ 1 & 0 & 0 \end {bmatrix} \)

While

\(P_{3}=\begin {bmatrix} 0 & 1 & 0 & 0\\ 1 & 0 & 0 & 0\\ 0 & 0 & 1 & 0\\ 0 & 0 & 0 & 1 \end {bmatrix} ,P_{4}=\begin {bmatrix} 1 & 0 & 0 & 0\\ 0 & 1 & 0 & 0\\ 0 & 0 & 0 & 1\\ 0 & 0 & 1 & 0 \end {bmatrix} \Rightarrow P_{3}P_{4}=P_{4}P_{3}=\begin {bmatrix} 0 & 1 & 0 & 0\\ 1 & 0 & 0 & 0\\ 0 & 0 & 0 & 1\\ 0 & 0 & 1 & 0 \end {bmatrix} \)