2.E: Exercises
( \newcommand{\kernel}{\mathrm{null}\,}\)
For the following pairs of matrices, determine if the sum A + B is defined. If so, find the sum.
- A = \left [ \begin{array}{rr} 1 & 0 \\ 0 & 1 \end{array} \right ], B = \left [ \begin{array}{rr} 0 & 1 \\ 1 & 0 \end{array} \right ]
- A = \left [ \begin{array}{rrr} 2 & 1 & 2 \\ 1 & 1 & 0 \end{array} \right ], B = \left [ \begin{array}{rrr} -1 & 0 & 3\\ 0 & 1 & 4 \end{array} \right ]
- A = \left [ \begin{array}{rr} 1 & 0 \\ -2 & 3 \\ 4 & 2 \end{array} \right ], B = \left [ \begin{array}{rrr} 2 & 7 & -1 \\ 0 & 3 & 4 \end{array} \right ]
For each matrix A, find the matrix -A such that A + (-A) = 0.
- A = \left [ \begin{array}{rr} 1 & 2 \\ 2 & 1 \end{array} \right ]
- A = \left [ \begin{array}{rr} -2 & 3 \\ 0 & 2 \end{array} \right ]
- A = \left [ \begin{array}{rrr} 0 & 1 & 2 \\ 1 & -1 & 3 \\ 4 & 2 & 0 \end{array} \right ]
In the context of Proposition 2.1.1, describe -A and 0.
- Answer
-
To get -A, just replace every entry of A with its additive inverse. The 0 matrix is the one which has all zeros in it.
2.1.2: Scalar Multiplication of Matrices
For each matrix A, find the product (-2)A, 0A, and 3A.
- A = \left [ \begin{array}{rr} 1 & 2 \\ 2 & 1 \end{array} \right ]
- A = \left [ \begin{array}{rr} -2 & 3 \\ 0 & 2 \end{array} \right ]
- A = \left [ \begin{array}{rrr} 0 & 1 & 2 \\ 1 & -1 & 3 \\ 4 & 2 & 0 \end{array} \right ]
Using only the properties given in Proposition 2.1.1 and Proposition 2.1.2, show -A is unique.
- Answer
-
Suppose B also works. Then -A=-A+\left( A+B\right) =\left( -A+A\right) +B=0+B=B\nonumber
Using only the properties given in Proposition 2.1.1 and Proposition 2.1.2, show 0 is unique.
- Answer
-
Suppose 0^{\prime } also works. Then 0^{\prime }=0^{\prime }+0=0.
Using only the properties given in Proposition 2.1.1 and Proposition 2.1.2 show 0A=0. Here the 0 on the left is the scalar 0 and the 0 on the right is the zero matrix of appropriate size.
- Answer
-
0A=\left( 0+0\right) A=0A+0A. Now add -\left( 0A\right) to both sides. Then 0=0A.
Using only the properties given in Proposition 2.1.1 and Proposition 2.1.2, as well as previous problems show \left( -1\right) A=-A.
- Answer
-
A+\left( -1\right) A=\left( 1+\left( -1\right) \right) A=0A=0. Therefore, from the uniqueness of the additive inverse proved in the above Problem \PageIndex{7}, it follows that -A=\left( -1\right) A.
2.2
Consider the matrices A =\left [ \begin{array}{rrr} 1 & 2 & 3 \\ 2 & 1 & 7 \end{array} \right ], B=\left [ \begin{array}{rrr} 3 & -1 & 2 \\ -3 & 2 & 1 \end{array} \right ], C =\left [ \begin{array}{rr} 1 & 2 \\ 3 & 1 \end{array} \right ], \\ D=\left [ \begin{array}{rr} -1 & 2 \\ 2 & -3 \end{array} \right ], E=\left [ \begin{array}{r} 2 \\ 3 \end{array} \right ].
Find the following if possible. If it is not possible explain why.
- -3A
- 3B-A
- AC
- CB
- AE
- EA
- Answer
-
- \left [ \begin{array}{rrr} -3 & -6 & -9 \\ -6 & -3 & -21 \end{array} \right ]
- \left [ \begin{array}{rrr} 8 & -5 & 3 \\ -11 & 5 & -4 \end{array} \right ]
- Not possible
- \left [ \begin{array}{rrr} -3 & 3 & 4 \\ 6 & -1 & 7 \end{array} \right ]
- Not possible
- Not possible
Consider the matrices A =\left [ \begin{array}{rr} 1 & 2 \\ 3 & 2 \\ 1 & -1 \end{array} \right ], B=\left [ \begin{array}{rrr} 2 & -5 & 2 \\ -3 & 2 & 1 \end{array} \right ] , C =\left [ \begin{array}{rr} 1 & 2 \\ 5 & 0 \end{array} \right ], \\ D=\left [ \begin{array}{rr} -1 & 1 \\ 4 & -3 \end{array} \right ], E=\left [ \begin{array}{r} 1 \\ 3 \end{array} \right ]
Find the following if possible. If it is not possible explain why.
- -3A
- 3B-A
- AC
- CA
- AE
- EA
- BE
- DE
- Answer
-
- \left [ \begin{array}{rr} -3 & -6 \\ -9 & -6 \\ -3 & 3 \end{array} \right ]
- Not possible.
- \left [ \begin{array}{rr} 11 & 2 \\ 13 & 6 \\ -4 & 2 \end{array} \right ]
- Not possible.
- \left [ \begin{array}{r} 7 \\ 9 \\ -2 \end{array} \right ]
- Not possible.
- Not possible.
- \left [ \begin{array}{r} 2 \\ -5 \end{array} \right ]
Let A=\left [ \begin{array}{rr} 1 & 1 \\ -2 & -1 \\ 1 & 2 \end{array} \right ], B=\left [ \begin{array}{rrr} 1 & -1 & -2 \\ 2 & 1 & -2 \end{array} \right ] , and C=\left [ \begin{array}{rrr} 1 & 1 & -3 \\ -1 & 2 & 0 \\ -3 & -1 & 0 \end{array} \right ] . Find the following if possible.
- AB
- BA
- AC
- CA
- CB
- BC
- Answer
-
- \left [ \begin{array}{rrr} 3 & 0 & -4 \\ -4 & 1 & 6 \\ 5 & 1 & -6 \end{array} \right ]
- \left [ \begin{array}{rr} 1 & -2 \\ -2 & -3 \end{array} \right ]
- Not possible
- \left [ \begin{array}{rr} -4 & -6 \\ -5 & -3 \\ -1 & -2 \end{array} \right ]
- \left [ \begin{array}{rrr} 8 & 1 & -3 \\ 7 & 6 & -6 \end{array} \right ]
Let A=\left [ \begin{array}{rr} -1 & -1 \\ 3 & 3 \end{array} \right ]. Find all 2\times 2 matrices, B such that AB=0.
- Answer
-
\begin{aligned} \left [ \begin{array}{rr} -1 & -1 \\ 3 & 3 \end{array} \right ] \left [ \begin{array}{cc} x & y \\ z & w \end{array} \right ] &=\left [ \begin{array}{cc} -x-z & -w-y \\ 3x+3z & 3w+3y \end{array} \right ] \\ &=\left [ \begin{array}{cc} 0 & 0 \\ 0 & 0 \end{array} \right ]\end{aligned} Solution is: w=-y,x=-z so the matrices are of the form \left [ \begin{array}{rr} x & y \\ -x & -y \end{array} \right ].
Let X=\left [ \begin{array}{rrr} -1 & -1 & 1 \end{array} \right ] and Y=\left [ \begin{array}{rrr} 0 & 1 & 2 \end{array} \right ] . Find X^{T}Y and XY^{T} if possible.
- Answer
-
X^{T}Y = \left [ \begin{array}{rrr} 0 & -1 & -2 \\ 0 & -1 & -2 \\ 0 & 1 & 2 \end{array} \right ] , XY^{T} = 1
Let A=\left [ \begin{array}{rr} 1 & 2 \\ 3 & 4 \end{array} \right ] ,B=\left [ \begin{array}{rr} 1 & 2 \\ 3 & k \end{array} \right ] . Is it possible to choose k such that AB=BA? If so, what should k equal?
- Answer
-
\begin{aligned} \left [ \begin{array}{cc} 1 & 2 \\ 3 & 4 \end{array} \right ] \left [ \begin{array}{cc} 1 & 2 \\ 3 & k \end{array} \right ] &= \left [ \begin{array}{cc} 7 & 2k+2 \\ 15 & 4k+6 \end{array} \right ] \\ \left [ \begin{array}{cc} 1 & 2 \\ 3 & k \end{array} \right ] \left [ \begin{array}{cc} 1 & 2 \\ 3 & 4 \end{array} \right ] &= \left [ \begin{array}{cc} 7 & 10 \\ 3k+3 & 4k+6 \end{array} \right ]\end{aligned} Thus you must have \begin{array}{c} 3k+3=15 \\ 2k+2=10 \end{array}, Solution is: \left[ k=4\right]
Let A=\left [ \begin{array}{rr} 1 & 2 \\ 3 & 4 \end{array} \right ] ,B=\left [ \begin{array}{rr} 1 & 2 \\ 1 & k \end{array} \right ] . Is it possible to choose k such that AB=BA? If so, what should k equal?
- Answer
-
\begin{aligned} \left [ \begin{array}{cc} 1 & 2 \\ 3 & 4 \end{array} \right ] \left [ \begin{array}{cc} 1 & 2 \\ 1 & k \end{array} \right ] &= \left [ \begin{array}{cc} 3 & 2k+2 \\ 7 & 4k+6 \end{array} \right ] \\ \left [ \begin{array}{cc} 1 & 2 \\ 1 & k \end{array} \right ] \left [ \begin{array}{cc} 1 & 2 \\ 3 & 4 \end{array} \right ] &= \left [ \begin{array}{cc} 7 & 10 \\ 3k+1 & 4k+2 \end{array} \right ]\end{aligned} However, 7\neq 3 and so there is no possible choice of k which will make these matrices commute.
Find 2\times 2 matrices, A, B, and C such that A\neq 0,C\neq B, but AC=AB.
- Answer
-
Let A=\left[\begin{array}{cc}1&-1 \\ -1&1\end{array}\right],\: B=\left[\begin{array}{cc}1&1\\1&1\end{array}\right],\: C=\left[\begin{array}{cc}2&2\\2&2\end{array}\right]. \begin{aligned}\left[\begin{array}{cc}1&-1\\-1&1\end{array}\right]\left[\begin{array}{cc}1&1\\1&1\end{array}\right]&=\left[\begin{array}{cc}0&0\\0&0\end{array}\right] \\ \left[\begin{array}{cc}1&-1\\-1&1\end{array}\right]\left[\begin{array}{cc}2&2\\2&2\end{array}\right]&=\left[\begin{array}{cc}0&0\\0&0\end{array}\right] \end{aligned}
Give an example of matrices (of any size), A,B,C such that B\neq C, A\neq 0, and yet AB=AC.
Find 2 \times 2 matrices A and B such that A \neq 0 and B \neq 0 but AB = 0.
- Answer
-
Let A=\left[\begin{array}{cc}1&-1 \\ -1&1\end{array}\right],\: B=\left[\begin{array}{cc}1&1\\1&1\end{array}\right]. \left[\begin{array}{cc}1&-1\\-1&1\end{array}\right]\left[\begin{array}{cc}1&1\\1&1\end{array}\right]=\left[\begin{array}{cc}0&0\\0&0\end{array}\right]\nonumber
Give an example of matrices (of any size), A,B such that A \neq 0 and B \neq 0 but AB=0.
Find 2 \times 2 matrices A and B such that A \neq 0 and B \neq 0 with AB \neq BA.
- Answer
-
Let A=\left[\begin{array}{cc}0&1\\1&0\end{array}\right],\: B=\left[\begin{array}{cc}1&2\\3&4\end{array}\right]. \begin{aligned}\left[\begin{array}{cc}0&1\\1&0\end{array}\right]\left[\begin{array}{cc}1&2\\3&4\end{array}\right]&=\left[\begin{array}{cc}3&4\\1&2\end{array}\right] \\ \left[\begin{array}{cc}1&2\\3&4\end{array}\right]\left[\begin{array}{cc}0&1\\1&0\end{array}\right]&=\left[\begin{array}{cc}2&1\\4&3\end{array}\right]\end{aligned}
Write the system \begin{array}{c} x_{1}-x_{2}+2x_{3} \\ 2x_{3}+x_{1} \\ 3x_{3} \\ 3x_{4}+3x_{2}+x_{1} \end{array}\nonumber in the form A\left [ \begin{array}{c} x_{1} \\ x_{2} \\ x_{3} \\ x_{4} \end{array} \right ] where A is an appropriate matrix.
- Answer
-
A=\left [ \begin{array}{rrrr} 1 & -1 & 2 & 0 \\ 1 & 0 & 2 & 0 \\ 0 & 0 & 3 & 0 \\ 1 & 3 & 0 & 3 \end{array} \right ]
Write the system \begin{array}{c} x_{1}+3x_{2}+2x_{3} \\ 2x_{3}+x_{1} \\ 6x_{3} \\ x_{4}+3x_{2}+x_{1} \end{array}\nonumber in the form A\left [ \begin{array}{c} x_{1} \\ x_{2} \\ x_{3} \\ x_{4} \end{array} \right ] where A is an appropriate matrix.
- Answer
-
A=\left [ \begin{array}{rrrr} 1 & 3 & 2 & 0 \\ 1 & 0 & 2 & 0 \\ 0 & 0 & 6 & 0 \\ 1 & 3 & 0 & 1 \end{array} \right ]
Write the system \begin{array}{c} x_{1}+x_{2}+x_{3} \\ 2x_{3}+x_{1}+x_{2} \\ x_{3}-x_{1} \\ 3x_{4}+x_{1} \end{array}\nonumber in the form A\left [ \begin{array}{c} x_{1} \\ x_{2} \\ x_{3} \\ x_{4} \end{array} \right ] where A is an appropriate matrix.
- Answer
-
A=\left [ \begin{array}{rrrr} 1 & 1 & 1 & 0 \\ 1 & 1 & 2 & 0 \\ -1 & 0 & 1 & 0 \\ 1 & 0 & 0 & 3 \end{array} \right ]
A matrix A is called idempotent if A^{2}=A. Let A= \left [ \begin{array}{rrr} 2 & 0 & 2 \\ 1 & 1 & 2 \\ -1 & 0 & -1 \end{array} \right ]\nonumber and show that A is idempotent.
2.3
For each pair of matrices, find the (1,2)-entry and (2,3)-entry of the product AB.
- A = \left [ \begin{array}{rrr} 1 & 2 & -1 \\ 3 & 4 & 0 \\ 2 & 5 & 1 \end{array} \right ], B = \left [ \begin{array}{rrr} 4 & 6 & -2 \\ 7 & 2 & 1 \\ -1 & 0 & 0 \end{array} \right ]
- A = \left [ \begin{array}{rrr} 1 & 3 & 1 \\ 0 & 2 & 4 \\ 1 & 0 & 5 \end{array} \right ], B = \left [ \begin{array}{rrr} 2 & 3 & 0 \\ -4 & 16 & 1 \\ 0 & 2 & 2 \end{array} \right ]
2.4
Suppose A and B are square matrices of the same size. Which of the following are necessarily true?
- \left( A-B\right) ^{2}=A^{2}-2AB+B^{2}
- \left( AB\right) ^{2}=A^{2}B^{2}
- \left( A+B\right) ^{2}=A^{2}+2AB+B^{2}
- \left( A+B\right) ^{2}=A^{2}+AB+BA+B^{2}
- A^{2}B^{2}=A\left( AB\right) B
- \left( A+B\right) ^{3}=A^{3}+3A^{2}B+3AB^{2}+B^{3}
- \left( A+B\right) \left( A-B\right) =A^{2}-B^{2}
- Answer
-
- Not necessarily true.
- Not necessarily true.
- Not necessarily true.
- Necessarily true.
- Necessarily true.
- Not necessarily true.
- Not necessarily true.
2.5
Consider the matrices A =\left [ \begin{array}{rr} 1 & 2 \\ 3 & 2 \\ 1 & -1 \end{array} \right ], B=\left [ \begin{array}{rrr} 2 & -5 & 2 \\ -3 & 2 & 1 \end{array} \right ], C =\left [ \begin{array}{rr} 1 & 2 \\ 5 & 0 \end{array} \right ], \\ D=\left [ \begin{array}{rr} -1 & 1 \\ 4 & -3 \end{array} \right ], E=\left [ \begin{array}{r} 1 \\ 3 \end{array} \right ]
Find the following if possible. If it is not possible explain why.
- -3A{^T}
- 3B - A^{T}
- E^{T}B
- EE^{T}
- B^{T}B
- CA^{T}
- D^{T}BE
- Answer
-
- \left [ \begin{array}{rrr} -3 & -9 & -3 \\ -6 & -6 & 3 \end{array} \right ]
- \left [ \begin{array}{rrr} 5 & -18 & 5 \\ -11 & 4 & 4 \end{array} \right ]
- \left [ \begin{array}{rrr} -7 & 1 & 5 \end{array} \right ]
- \left [ \begin{array}{rr} 1 & 3 \\ 3 & 9 \end{array} \right ]
- \left [ \begin{array}{rrr} 13 & -16 & 1\\ -16 & 29 & -8 \\ 1 & -8 & 5 \end{array} \right ]
- \left [ \begin{array}{rrr} 5 & 7 & -1 \\ 5 & 15 & 5 \end{array} \right ]
- Not possible.
Let A be an n\times n matrix. Show A equals the sum of a symmetric and a skew symmetric matrix.
- Hint
-
Show that \frac{1}{2}\left( A^{T}+A\right) is symmetric and then consider using this as one of the matrices.
Show that the main diagonal of every skew symmetric matrix consists of only zeros. Recall that the main diagonal consists of every entry of the matrix which is of the form a_{ii}.
- Answer
-
If A is symmetric then A=-A^{T}. It follows that a_{ii}=-a_{ii} and so each a_{ii}=0.
Prove 3 from Lemma 2.5.1. That is, show that for an m \times n matrix A, an m \times n matrix B, and scalars r, s, the following holds: \left( rA + sB \right) ^T = rA^{T} + sB^{T}\nonumber
2.6
Prove that I_{m}A=A where A is an m\times n matrix.
- Answer
-
\left( I_{m}A\right) _{ij}\equiv \sum_{j}\delta _{ik}A_{kj}=A_{ij}
Suppose AB=AC and A is an invertible n\times n matrix. Does it follow that B=C? Explain why or why not.
- Answer
-
Yes B=C. Multiply AB = AC on the left by A^{-1}.
Suppose AB=AC and A is a non invertible n\times n matrix. Does it follow that B=C? Explain why or why not.
Give an example of a matrix A such that A^{2}=I and yet A\neq I and A\neq -I.
- Answer
-
A = \left [ \begin{array}{rrr} 1 & 0 & 0 \\ 0 & -1 & 0 \\ 0 & 0 & 1 \end{array} \right ]
2.7
Let A=\left [ \begin{array}{rr} 2 & 1 \\ -1 & 3 \end{array} \right ]\nonumber Find A^{-1} if possible. If A^{-1} does not exist, explain why.
- Answer
-
\left [ \begin{array}{rr} 2 & 1 \\ -1 & 3 \end{array} \right ]^{-1}= \left [ \begin{array}{rr} \frac{3}{7} & -\frac{1}{7} \\ \frac{1}{7} & \frac{2}{7} \end{array} \right ]
Let A=\left [ \begin{array}{rr} 0 & 1 \\ 5 & 3 \end{array} \right ]\nonumber Find A^{-1} if possible. If A^{-1} does not exist, explain why.
- Answer
-
\left [ \begin{array}{cc} 0 & 1 \\ 5 & 3 \end{array} \right ]^{-1}= \left [ \begin{array}{cc} -\frac{3}{5} & \frac{1}{5} \\ 1 & 0 \end{array} \right ]
Add exercises text here.Let A=\left [ \begin{array}{rr} 2 & 1 \\ 3 & 0 \end{array} \right ]\nonumber Find A^{-1} if possible. If A^{-1} does not exist, explain why.
- Answer
-
\left [ \begin{array}{cc} 2 & 1 \\ 3 & 0 \end{array} \right ]^{-1}= \left [ \begin{array}{cc} 0 & \frac{1}{3} \\ 1 & -\frac{2}{3} \end{array} \right ]
Let A=\left [ \begin{array}{rr} 2 & 1 \\ 4 & 2 \end{array} \right ]\nonumber Find A^{-1} if possible. If A^{-1} does not exist, explain why.
- Answer
-
\left [ \begin{array}{cc} 2 & 1 \\ 4 & 2 \end{array} \right ]^{-1} does not exist. The of this matrix is \left [ \begin{array}{cc} 1 & \frac{1}{2} \\ 0 & 0 \end{array} \right ]
Let A be a 2\times 2 invertible matrix, with A=\left [ \begin{array}{cc} a & b \\ c & d \end{array} \right ] . Find a formula for A^{-1} in terms of a,b,c,d.
- Answer
-
\left [ \begin{array}{cc} a & b \\ c & d \end{array} \right ]^{-1}= \left [ \begin{array}{cc} \frac{d}{ad-bc} & -\frac{b}{ad-bc} \\ -\frac{c}{ad-bc} & \frac{a}{ad-bc} \end{array} \right ]
Let A=\left [ \begin{array}{rrr} 1 & 2 & 3 \\ 2 & 1 & 4 \\ 1 & 0 & 2 \end{array} \right ]\nonumber Find A^{-1} if possible. If A^{-1} does not exist, explain why.
- Answer
-
\left [ \begin{array}{ccc} 1 & 2 & 3 \\ 2 & 1 & 4 \\ 1 & 0 & 2 \end{array} \right ]^{-1}= \left [ \begin{array}{rrr} -2 & 4 & -5 \\ 0 & 1 & -2 \\ 1 & -2 & 3 \end{array} \right ]
Let A=\left [ \begin{array}{rrr} 1 & 0 & 3 \\ 2 & 3 & 4 \\ 1 & 0 & 2 \end{array} \right ]\nonumber Find A^{-1} if possible. If A^{-1} does not exist, explain why.
- Answer
-
\left [ \begin{array}{ccc} 1 & 0 & 3 \\ 2 & 3 & 4 \\ 1 & 0 & 2 \end{array} \right ]^{-1}= \left [ \begin{array}{rrr} -2 & 0 & 3 \\ 0 & \frac{1}{3} & -\frac{2}{3} \\ 1 & 0 & -1 \end{array} \right ]
Let A=\left [ \begin{array}{rrr} 1 & 2 & 3 \\ 2 & 1 & 4 \\ 4 & 5 & 10 \end{array} \right ]\nonumber Find A^{-1} if possible. If A^{-1} does not exist, explain why.
- Answer
-
The reduced row-echelon form is \left [ \begin{array}{ccc} 1 & 0 & \frac{5}{3} \\ 0 & 1 & \frac{2}{3} \\ 0 & 0 & 0 \end{array} \right ]. There is no inverse.
Let A=\left [ \begin{array}{rrrr} 1 & 2 & 0 & 2 \\ 1 & 1 & 2 & 0 \\ 2 & 1 & -3 & 2 \\ 1 & 2 & 1 & 2 \end{array} \right ]\nonumber Find A^{-1} if possible. If A^{-1} does not exist, explain why.
- Answer
-
\left [ \begin{array}{rrrr} 1 & 2 & 0 & 2 \\ 1 & 1 & 2 & 0 \\ 2 & 1 & -3 & 2 \\ 1 & 2 & 1 & 2 \end{array} \right ]^{-1}= \left [ \begin{array}{rrrr} -1 & \frac{1}{2} & \frac{1}{2} & \frac{1}{2} \\ 3 & \frac{1}{2} & - \frac{1}{2} & - \frac{5}{2} \\ -1 & 0 & 0 & 1 \\ -2 & - \frac{3}{4} & \frac{1}{4} & \frac{9}{4} \end{array} \right ]
Using the inverse of the matrix, find the solution to the systems:
- \left [ \begin{array}{rr} 2 & 4 \\ 1 & 1 \end{array} \right ] \left [ \begin{array}{c} x \\ y \end{array} \right ] =\left [ \begin{array}{r} 1 \\ 2 \end{array} \right ]\nonumber
- \left [ \begin{array}{rr} 2 & 4 \\ 1 & 1 \end{array} \right ] \left [ \begin{array}{c} x \\ y \end{array} \right ] =\left [ \begin{array}{r} 2 \\ 0 \end{array} \right ]\nonumber
Now give the solution in terms of a and b to \left [ \begin{array}{rr} 2 & 4 \\ 1 & 1 \end{array} \right ] \left [ \begin{array}{c} x \\ y \end{array}\right ] = \left [ \begin{array}{c} a \\ b \end{array} \right ]\nonumber
Using the inverse of the matrix, find the solution to the systems:
- \left [ \begin{array}{rrr} 1 & 0 & 3 \\ 2 & 3 & 4 \\ 1 & 0 & 2 \end{array} \right ] \left [ \begin{array}{c} x \\ y \\ z \end{array} \right ] =\left [ \begin{array}{r} 1 \\ 0 \\ 1 \end{array} \right ]\nonumber
- \left [ \begin{array}{rrr} 1 & 0 & 3 \\ 2 & 3 & 4 \\ 1 & 0 & 2 \end{array} \right ] \left [ \begin{array}{c} x \\ y \\ z \end{array} \right ] =\left [ \begin{array}{r} 3 \\ -1 \\ -2 \end{array} \right ]\nonumber
Now give the solution in terms of a,b, and c to the following: \left [ \begin{array}{rrr} 1 & 0 & 3 \\ 2 & 3 & 4 \\ 1 & 0 & 2 \end{array} \right ] \left [ \begin{array}{c} x \\ y \\ z \end{array} \right ] =\left [ \begin{array}{c} a \\ b \\ c \end{array} \right ]\nonumber
- Answer
-
- \left [ \begin{array}{c} x \\ y \\ z \end{array} \right ] =\left [ \begin{array}{c} 1 \\ -\frac{2}{3} \\ 0 \end{array} \right ]
- \left [ \begin{array}{c} x \\ y \\ z \end{array} \right ] = \left [ \begin{array}{r} -12 \\ 1 \\ 5 \end{array} \right ]
- \left [ \begin{array}{c} x \\ y \\ z \end{array} \right ] = \left [ \begin{array}{c} 3c-2a \\ \frac{1}{3}b-\frac{2}{3}c \\ a-c \end{array} \right ]
Show that if A is an n\times n invertible matrix and X is a n\times 1 matrix such that AX=B for B an n\times 1 matrix, then X=A^{-1}B.
- Answer
-
Multiply both sides of AX=B on the left by A^{-1}.
Prove that if A^{-1} exists and AX=0 then X=0.
- Answer
-
Multiply on both sides on the left by A^{-1}. Thus 0=A^{-1}0=A^{-1}\left( AX\right) =\left( A^{-1}A\right) X=IX = X\nonumber
Show that if A^{-1} exists for an n\times n matrix, then it is unique. That is, if BA=I and AB=I, then B=A^{-1}.
- Answer
-
A^{-1}=A^{-1}I=A^{-1}\left( AB\right) =\left( A^{-1}A\right) B=IB=B.
Show that if A is an invertible n\times n matrix, then so is A^{T} and \left( A^{T}\right) ^{-1}=\left( A^{-1}\right) ^{T}.
- Answer
-
You need to show that \left( A^{-1}\right) ^{T} acts like the inverse of A^{T} because from uniqueness in the above problem, this will imply it is the inverse. From properties of the transpose, \begin{aligned} A^{T}\left( A^{-1}\right) ^{T} &=\left( A^{-1}A\right) ^{T}=I^{T}=I \\ \left( A^{-1}\right) ^{T}A^{T} &=\left( AA^{-1}\right) ^{T}=I^{T}=I\end{aligned} Hence \left( A^{-1}\right) ^{T}=\left( A^{T}\right) ^{-1} and this last matrix exists.
Show \left( AB\right) ^{-1}=B^{-1}A^{-1} by verifying that AB\left( B^{-1}A^{-1}\right) =I\nonumber and B^{-1}A^{-1}\left( AB\right) =I\nonumber Hint: Use Problem \PageIndex{48}.
- Answer
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\left( AB\right) B^{-1}A^{-1}=A\left( BB^{-1}\right) A^{-1}=AA^{-1}=I B^{-1}A^{-1}\left( AB\right) =B^{-1}\left( A^{-1}A\right) B=B^{-1}IB=B^{-1}B=I
Show that \left( ABC\right) ^{-1}=C^{-1}B^{-1}A^{-1} by verifying that \left( ABC\right) \left( C^{-1}B^{-1}A^{-1}\right) =I\nonumber and \left( C^{-1}B^{-1}A^{-1}\right)\left( ABC\right) =I\nonumber Hint: Use Problem \PageIndex{48}.
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The proof of this exercise follows from the previous one.
If A is invertible, show \left( A^{2}\right) ^{-1}=\left( A^{-1}\right) ^{2}. Hint: Use Problem \PageIndex{48}.
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A^{2}\left( A^{-1}\right) ^{2}=AAA^{-1}A^{-1}=AIA^{-1}=AA^{-1}=I \left( A^{-1}\right) ^{2}A^{2}=A^{-1}A^{-1}AA=A^{-1}IA=A^{-1}A=I
If A is invertible, show \left( A^{-1}\right) ^{-1}=A. Hint: Use Problem \PageIndex{48}.
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A^{-1}A=AA^{-1}=I and so by uniqueness, \left( A^{-1}\right) ^{-1}=A.
2.8
Let A = \left [ \begin{array}{rr} 2 & 3 \\ 1 & 2 \end{array}\right ]. Suppose a row operation is applied to A and the result is B = \left [ \begin{array}{rr} 1 & 2 \\ 2 & 3 \end{array}\right ]. Find the elementary matrix E that represents this row operation.
Let A = \left [ \begin{array}{rr} 4 & 0 \\ 2 & 1 \end{array}\right ]. Suppose a row operation is applied to A and the result is B = \left [ \begin{array}{rr} 8 & 0 \\ 2 & 1 \end{array}\right ]. Find the elementary matrix E that represents this row operation.
Let A = \left [ \begin{array}{rr} 1 & -3 \\ 0 & 5 \end{array}\right ]. Suppose a row operation is applied to A and the result is B = \left [ \begin{array}{rr} 1 & -3 \\ 2 & -1 \end{array}\right ]. Find the elementary matrix E that represents this row operation.
Let A = \left [ \begin{array}{rrr} 1 & 2 & 1 \\ 0 & 5 & 1 \\ 2 & -1 & 4 \end{array}\right ]. Suppose a row operation is applied to A and the result is B = \left [ \begin{array}{rrr} 1 & 2 & 1\\ 2 & -1 & 4 \\ 0 & 5 & 1 \end{array}\right ].
- Find the elementary matrix E such that EA = B.
- Find the inverse of E, E^{-1}, such that E^{-1}B = A.
Let A = \left [ \begin{array}{rrr} 1 & 2 & 1 \\ 0 & 5 & 1 \\ 2 & -1 & 4 \end{array}\right ]. Suppose a row operation is applied to A and the result is B = \left [ \begin{array}{rrr} 1 & 2 & 1\\ 0 & 10 & 2 \\ 2 & -1 & 4 \end{array}\right ].
- Find the elementary matrix E such that EA = B.
- Find the inverse of E, E^{-1}, such that E^{-1}B = A.
Let A = \left [ \begin{array}{rrr} 1 & 2 & 1 \\ 0 & 5 & 1 \\ 2 & -1 & 4 \end{array}\right ]. Suppose a row operation is applied to A and the result is B = \left [ \begin{array}{rrr} 1 & 2 & 1\\ 0 & 5 & 1 \\ 1 & -\frac{1}{2} & 2 \end{array}\right ].
- Find the elementary matrix E such that EA = B.
- Find the inverse of E, E^{-1}, such that E^{-1}B = A.
Let A = \left [ \begin{array}{rrr} 1 & 2 & 1 \\ 0 & 5 & 1 \\ 2 & -1 & 4 \end{array}\right ]. Suppose a row operation is applied to A and the result is B = \left [ \begin{array}{rrr} 1 & 2 & 1\\ 2 & 4 & 5 \\ 2 & -1 & 4 \end{array}\right ].
- Find the elementary matrix E such that EA = B.
- Find the inverse of E, E^{-1}, such that E^{-1}B = A.
2.10
Find an LU factorization of \left [ \begin{array}{rrr} 1 & 2 & 0 \\ 2 & 1 & 3 \\ 1 & 2 & 3 \end{array} \right ] .
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\left [ \begin{array}{ccc} 1 & 2 & 0 \\ 2 & 1 & 3 \\ 1 & 2 & 3 \end{array} \right ] = \left [ \begin{array}{ccc} 1 & 0 & 0 \\ 2 & 1 & 0 \\ 1 & 0 & 1 \end{array} \right ] \left [ \begin{array}{rrr} 1 & 2 & 0 \\ 0 & -3 & 3 \\ 0 & 0 & 3 \end{array} \right ]\nonumber
Find an LU factorization of \left [ \begin{array}{rrrr} 1 & 2 & 3 & 2 \\ 1 & 3 & 2 & 1 \\ 5 & 0 & 1 & 3 \end{array} \right ] .
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\left [ \begin{array}{cccc} 1 & 2 & 3 & 2 \\ 1 & 3 & 2 & 1 \\ 5 & 0 & 1 & 3 \end{array} \right ] = \left [ \begin{array}{rrr} 1 & 0 & 0 \\ 1 & 1 & 0 \\ 5 & -10 & 1 \end{array} \right ] \left [ \begin{array}{rrrr} 1 & 2 & 3 & 2 \\ 0 & 1 & -1 & -1 \\ 0 & 0 & -24 & -17 \end{array} \right ]\nonumber
Find an LU factorization of the matrix \left [ \begin{array}{rrrr} 1 & -2 & -5 & 0 \\ -2 & 5 & 11 & 3 \\ 3 & -6 & -15 & 1 \end{array} \right ] .
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\left [ \begin{array}{rrrr} 1 & -2 & -5 & 0 \\ -2 & 5 & 11 & 3 \\ 3 & -6 & -15 & 1 \end{array} \right ] = \left [ \begin{array}{rrr} 1 & 0 & 0 \\ -2 & 1 & 0 \\ 3 & 0 & 1 \end{array} \right ] \left [ \begin{array}{rrrr} 1 & -2 & -5 & 0 \\ 0 & 1 & 1 & 3 \\ 0 & 0 & 0 & 1 \end{array} \right ]\nonumber
Find an LU factorization of the matrix \left [ \begin{array}{rrrr} 1 & -1 & -3 & -1 \\ -1 & 2 & 4 & 3 \\ 2 & -3 & -7 & -3 \end{array} \right ] .
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\left [ \begin{array}{rrrr} 1 & -1 & -3 & -1 \\ -1 & 2 & 4 & 3 \\ 2 & -3 & -7 & -3 \end{array} \right ] = \left [ \begin{array}{rrr} 1 & 0 & 0 \\ -1 & 1 & 0 \\ 2 & -1 & 1 \end{array} \right ] \left [ \begin{array}{rrrr} 1 & -1 & -3 & -1 \\ 0 & 1 & 1 & 2 \\ 0 & 0 & 0 & 1 \end{array} \right ]\nonumber
Find an LU factorization of the matrix \ \ \left [ \begin{array}{rrrr} 1 & -3 & -4 & -3 \\ -3 & 10 & 10 & 10 \\ 1 & -6 & 2 & -5 \end{array} \right ] .
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\left [ \begin{array}{rrrr} 1 & -3 & -4 & -3 \\ -3 & 10 & 10 & 10 \\ 1 & -6 & 2 & -5 \end{array} \right ] = \left [ \begin{array}{rrr} 1 & 0 & 0 \\ -3 & 1 & 0 \\ 1 & -3 & 1 \end{array} \right ] \left [ \begin{array}{rrrr} 1 & -3 & -4 & -3 \\ 0 & 1 & -2 & 1 \\ 0 & 0 & 0 & 1 \end{array} \right ]\nonumber
Find an LU factorization of the matrix \left [ \begin{array}{rrrr} 1 & 3 & 1 & -1 \\ 3 & 10 & 8 & -1 \\ 2 & 5 & -3 & -3 \end{array} \right ] .
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\left [ \begin{array}{rrrr} 1 & 3 & 1 & -1 \\ 3 & 10 & 8 & -1 \\ 2 & 5 & -3 & -3 \end{array} \right ] = \left [ \begin{array}{rrr} 1 & 0 & 0 \\ 3 & 1 & 0 \\ 2 & -1 & 1 \end{array} \right ] \left [ \begin{array}{rrrr} 1 & 3 & 1 & -1 \\ 0 & 1 & 5 & 2 \\ 0 & 0 & 0 & 1 \end{array} \right ]\nonumber
Find an LU factorization of the matrix \left [ \begin{array}{rrr} 3 & -2 & 1 \\ 9 & -8 & 6 \\ -6 & 2 & 2 \\ 3 & 2 & -7 \end{array} \right ] .
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\left [ \begin{array}{rrr} 3 & -2 & 1 \\ 9 & -8 & 6 \\ -6 & 2 & 2 \\ 3 & 2 & -7 \end{array} \right ] = \left [ \begin{array}{rrrr} 1 & 0 & 0 & 0 \\ 3 & 1 & 0 & 0 \\ -2 & 1 & 1 & 0 \\ 1 & -2 & -2 & 1 \end{array} \right ] \left [ \begin{array}{rrr} 3 & -2 & 1 \\ 0 & -2 & 3 \\ 0 & 0 & 1 \\ 0 & 0 & 0 \end{array} \right ]\nonumber
Find an LU factorization of the matrix \left [ \begin{array}{rrr} -3 & -1 & 3 \\ 9 & 9 & -12 \\ 3 & 19 & -16 \\ 12 & 40 & -26 \end{array} \right ] .
Find an LU factorization of the matrix \left [ \begin{array}{rrr} -1 & -3 & -1 \\ 1 & 3 & 0 \\ 3 & 9 & 0 \\ 4 & 12 & 16 \end{array} \right ] .
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\left [ \begin{array}{rrr} -1 & -3 & -1 \\ 1 & 3 & 0 \\ 3 & 9 & 0 \\ 4 & 12 & 16 \end{array} \right ] = \left [ \begin{array}{rrrr} 1 & 0 & 0 & 0 \\ -1 & 1 & 0 & 0 \\ -3 & 0 & 1 & 0 \\ -4 & 0 & -4 & 1 \end{array} \right ] \left [ \begin{array}{rrr} -1 & -3 & -1 \\ 0 & 0 & -1 \\ 0 & 0 & -3 \\ 0 & 0 & 0 \end{array} \right ]\nonumber
Find the LU factorization of the coefficient matrix using Dolittle’s method and use it to solve the system of equations. \begin{array}{c} x+2y=5 \\ 2x+3y=6 \end{array}\nonumber
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An LU factorization of the coefficient matrix is \left [ \begin{array}{cc} 1 & 2 \\ 2 & 3 \end{array} \right ] = \left [ \begin{array}{cc} 1 & 0 \\ 2 & 1 \end{array} \right ] \left [ \begin{array}{cc} 1 & 2 \\ 0 & -1 \end{array} \right ]\nonumber First solve \left [ \begin{array}{cc} 1 & 0 \\ 2 & 1 \end{array} \right ] \left [ \begin{array}{c} u \\ v \end{array} \right ] =\left [ \begin{array}{c} 5 \\ 6 \end{array} \right ]\nonumber which gives \left [ \begin{array}{c} u \\ v \end{array} \right ] = \left [ \begin{array}{r} 5 \\ -4 \end{array} \right ] . Then solve \left [ \begin{array}{rr} 1 & 2 \\ 0 & -1 \end{array} \right ] \left [ \begin{array}{c} x \\ y \end{array} \right ] =\left [ \begin{array}{r} 5 \\ -4 \end{array} \right ]\nonumber which says that y=4 and x=-3.
Find the LU factorization of the coefficient matrix using Dolittle’s method and use it to solve the system of equations. \begin{array}{c} x+2y+z=1 \\ y+3z=2 \\ 2x+3y=6 \end{array}\nonumber
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An LU factorization of the coefficient matrix is \left [ \begin{array}{rrr} 1 & 2 & 1 \\ 0 & 1 & 3 \\ 2 & 3 & 0 \end{array} \right ] = \left [ \begin{array}{rrr} 1 & 0 & 0 \\ 0 & 1 & 0 \\ 2 & -1 & 1 \end{array} \right ] \left [ \begin{array}{rrr} 1 & 2 & 1 \\ 0 & 1 & 3 \\ 0 & 0 & 1 \end{array} \right ]\nonumber First solve \left [ \begin{array}{rrr} 1 & 0 & 0 \\ 0 & 1 & 0 \\ 2 & -1 & 1 \end{array} \right ] \left [ \begin{array}{c} u \\ v \\ w \end{array} \right ] =\left [ \begin{array}{c} 1 \\ 2 \\ 6 \end{array} \right ]\nonumber which yields u=1,v=2,w=6. Next solve \left [ \begin{array}{rrr} 1 & 2 & 1 \\ 0 & 1 & 3 \\ 0 & 0 & 1 \end{array} \right ] \left [ \begin{array}{c} x \\ y \\ z \end{array} \right ] =\left [ \begin{array}{c} 1 \\ 2 \\ 6 \end{array} \right ]\nonumber This yields z=6,y=-16,x=27.
Find the LU factorization of the coefficient matrix using Dolittle’s method and use it to solve the system of equations. \begin{array}{c} x+2y+3z=5 \\ 2x+3y+z=6 \\ x-y+z=2 \end{array}\nonumber
Find the LU factorization of the coefficient matrix using Dolittle’s method and use it to solve the system of equations. \begin{array}{c} x+2y+3z=5 \\ 2x+3y+z=6 \\ 3x+5y+4z=11 \end{array}\nonumber
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An LU factorization of the coefficient matrix is \left [ \begin{array}{rrr} 1 & 2 & 3 \\ 2 & 3 & 1 \\ 3 & 5 & 4 \end{array} \right ] = \left [ \begin{array}{rrr} 1 & 0 & 0 \\ 2 & 1 & 0 \\ 3 & 1 & 1 \end{array} \right ] \left [ \begin{array}{rrr} 1 & 2 & 3 \\ 0 & -1 & -5 \\ 0 & 0 & 0 \end{array} \right ]\nonumber First solve \left [ \begin{array}{rrr} 1 & 0 & 0 \\ 2 & 1 & 0 \\ 3 & 1 & 1 \end{array} \right ] \left [ \begin{array}{c} u \\ v \\ w \end{array} \right ] =\left [ \begin{array}{c} 5 \\ 6 \\ 11 \end{array} \right ]\nonumber Solution is: \left [ \begin{array}{c} u \\ v \\ w \end{array} \right ] = \left [ \begin{array}{c} 5 \\ -4 \\ 0 \end{array} \right ] . Next solve \left [ \begin{array}{rrr} 1 & 2 & 3 \\ 0 & -1 & -5 \\ 0 & 0 & 0 \end{array} \right ] \left [ \begin{array}{c} x \\ y \\ z \end{array} \right ] =\left [ \begin{array}{c} 5 \\ -4 \\ 0 \end{array} \right ]\nonumber Solution is: \left [ \begin{array}{c} x \\ y \\ z \end{array} \right ] =\left [ \begin{array}{c} 7t-3 \\ 4-5t \\ t \end{array} \right ] ,t\in \mathbb{R}.
Is there only one LU factorization for a given matrix? Hint: Consider the equation \left [ \begin{array}{rr} 0 & 1 \\ 0 & 1 \end{array} \right ] =\left [ \begin{array}{rr} 1 & 0 \\ 1 & 1 \end{array} \right ] \left [ \begin{array}{rr} 0 & 1 \\ 0 & 0 \end{array} \right ] .\nonumber Look for all possible LU factorizations.
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Sometimes there is more than one LU factorization as is the case in this example. The given equation clearly gives an LU factorization. However, it appears that the following equation gives another LU factorization. \left [ \begin{array}{cc} 0 & 1 \\ 0 & 1 \end{array} \right ] =\left [ \begin{array}{cc} 1 & 0 \\ 0 & 1 \end{array} \right ] \left [ \begin{array}{cc} 0 & 1 \\ 0 & 1 \end{array} \right ]\nonumber