Quiz 2. The Vector Form For the General Solution / Transpose Matrices. Math 2568 Spring 2017.
Problem 273
(a) The given matrix is the augmented matrix for a system of linear equations.
Give the vector form for the general solution.
\[ \left[\begin{array}{rrrrr|r}
1 & 0 & -1 & 0 &-2 & 0 \\
0 & 1 & 2 & 0 & -1 & 0 \\
0 & 0 & 0 & 1 & 1 & 0 \\
\end{array} \right].\]
(b) Let
\[A=\begin{bmatrix}
1 & 2 & 3 \\
4 &5 &6
\end{bmatrix}, B=\begin{bmatrix}
1 & 0 & 1 \\
0 &1 &0
\end{bmatrix}, C=\begin{bmatrix}
1 & 2\\
0& 6
\end{bmatrix}, \mathbf{v}=\begin{bmatrix}
0 \\
1 \\
0
\end{bmatrix}.\]
Then compute and simplify the following expression.
\[\mathbf{v}^{\trans}\left( A^{\trans}-(A-B)^{\trans}\right)C.\]
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Solution.
(a) Give the vector form for the general solution
The system of linear equation represented by the augmented matrix is
\begin{align*}
x_1-x_3-2x_5&=0\\
x_2+2x_3-x_5&=0\\
x_4+x_5=0.
\end{align*}
Solving the preceding system, we obtain
\begin{align*}
x_1&=x_3+2x_5\\
x_2&=-2x_3+x_5\\
x_4&=-x_5.
\end{align*}
Here $x_2, x_5$ are free variables and the rest are dependent variables.
Hence the general solution $\mathbf{x}$ can be expressed as
\begin{align*}
\mathbf{x}&=\begin{bmatrix}
x_1 \\
x_2 \\
x_3 \\
x_4 \\
x_5
\end{bmatrix}=\begin{bmatrix}
x_3+2x_5 \\
-2x_3+x_5 \\
x_3 \\
-x_5 \\
x_5
\end{bmatrix}\\[10pt]
&=\begin{bmatrix}
x_3 \\
-2x_3 \\
x_3 \\
0 \\
0
\end{bmatrix}+\begin{bmatrix}
2x_5 \\
x_5 \\
0 \\
-x_5 \\
x_5
\end{bmatrix}=x_3\begin{bmatrix}
1 \\
-2 \\
1 \\
0 \\
0
\end{bmatrix}+x_5\begin{bmatrix}
2 \\
1 \\
0 \\
-1\\
1
\end{bmatrix}.
\end{align*}
Therefore, the vector form for the general solution is
\[\mathbf{x}=x_3\begin{bmatrix}
1 \\
-2 \\
1 \\
0 \\
0
\end{bmatrix}+x_5\begin{bmatrix}
2 \\
1 \\
0 \\
-1\\
1
\end{bmatrix}.\]
(b) Matrix product and transpose
First of all, note that by the property of the transpose we have
\[(A-B)^{\trans}=A^{\trans}-B^{\trans}.\]
Hence we can simply the middle part:
\begin{align*}
A^{\trans}-(A-B)^{\trans}&= A^{\trans}-(A^{\trans}-B^{\trans})\\
&=A^{\trans}-A^{\trans}+B^{\trans}=B^{\trans}.
\end{align*}
Thus the expression becomes
\[\mathbf{v}^{\trans}\left( A^{\trans}-(A-B)^{\trans}\right)C=\mathbf{v}^{\trans}B^{\trans}C.\]
The transposes of $\mathbf{v}$ and $B$ are
\[\mathbf{v}^{\trans}=\begin{bmatrix}
0 & 1 & 0 \\
\end{bmatrix} \text{ and } B^{\trans}=\begin{bmatrix}
1 & 0 \\
0 & 1 \\
1 &0
\end{bmatrix}.\]
Thus we have
\begin{align*}
&\mathbf{v}^{\trans}\left( A^{\trans}-(A-B)^{\trans}\right)C=\mathbf{v}^{\trans}B^{\trans}C\\
&=\begin{bmatrix}
0 & 1 & 0 \\
\end{bmatrix}
\begin{bmatrix}
1 & 0 \\
0 & 1 \\
1 &0
\end{bmatrix}
\begin{bmatrix}
1 & 2\\
0& 6
\end{bmatrix}\\
&=\begin{bmatrix}
0 & 1
\end{bmatrix}\begin{bmatrix}
1 & 2\\
0& 6
\end{bmatrix}
=\begin{bmatrix}
0 & 6
\end{bmatrix}.
\end{align*}
In conclusion, we have obtained
\[\mathbf{v}^{\trans}\left( A^{\trans}-(A-B)^{\trans}\right)C=\begin{bmatrix}
0 & 6
\end{bmatrix}.\]
Comment.
These are Quiz 2 problems for Math 2568 (Introduction to Linear Algebra) at OSU in Spring 2017.
List of Quiz Problems of Linear Algebra (Math 2568) at OSU in Spring 2017
There were 13 weekly quizzes. Here is the list of links to the quiz problems and solutions.
- Quiz 1. Gauss-Jordan elimination / homogeneous system.
- Quiz 2. The vector form for the general solution / Transpose matrices.
- Quiz 3. Condition that vectors are linearly dependent/ orthogonal vectors are linearly independent
- Quiz 4. Inverse matrix/ Nonsingular matrix satisfying a relation
- Quiz 5. Example and non-example of subspaces in 3-dimensional space
- Quiz 6. Determine vectors in null space, range / Find a basis of null space
- Quiz 7. Find a basis of the range, rank, and nullity of a matrix
- Quiz 8. Determine subsets are subspaces: functions taking integer values / set of skew-symmetric matrices
- Quiz 9. Find a basis of the subspace spanned by four matrices
- Quiz 10. Find orthogonal basis / Find value of linear transformation
- Quiz 11. Find eigenvalues and eigenvectors/ Properties of determinants
- Quiz 12. Find eigenvalues and their algebraic and geometric multiplicities
- Quiz 13 (Part 1). Diagonalize a matrix.
- Quiz 13 (Part 2). Find eigenvalues and eigenvectors of a special matrix
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