When performing matrix multiplication, especially with a column matrix and a row matrix, remember that the resulting matrix's dimensions are determined by the row count of the column matrix and the column count of the row matrix. The outer product of a \( m \times 1 \) and \( 1 \times n \) matrix results in a matrix of dimensions \( m \times n \). For transposing a matrix, simply swap the rows with columns, and this operation is essential for many matrix-related problems. Don't forget that matrix multiplication follows the distributive property, so you can multiply each element of the rows and columns accordingly.
To find \( (PQ)' \), we first compute the product \( PQ \) where:
The product \( PQ \) will be a \( 3 \times 3 \) matrix given by:
\[PQ = \begin{bmatrix}-1 \\2 \\1\end{bmatrix}\times\begin{bmatrix}2 & -4 & 1\end{bmatrix}=\begin{bmatrix}-2 & 4 & -1 \\4 & -8 & 2 \\2 & -4 & 1\end{bmatrix}\]
Next, we find the transpose \( (PQ)' \):
\[(PQ)' = \begin{bmatrix}-2 & 4 & -1 \\4 & -8 & 2 \\2 & -4 & 1\end{bmatrix}'=\begin{bmatrix}-2 & 4 & 2 \\4 & -8 & -4 \\-1 & 2 & 1\end{bmatrix}\]
Thus, the correct answer is:
\[\begin{bmatrix}-2 & 4 & 2 \\4 & -8 & -4 \\-1 & 2 & 1\end{bmatrix}\]
To solve for \((PQ)^T\), we need to perform several steps. First, compute the product of matrices \(P\) and \(Q\), then transpose the resulting matrix.
Given matrices:
\(P = \begin{bmatrix} -1 \\ 2 \\ 1 \end{bmatrix}\)
\(Q = \begin{bmatrix} 2 & -4 & 1 \end{bmatrix}\)
Step 1: Calculate \(PQ\).
Since \(P\) is a column matrix (3x1) and \(Q\) is a row matrix (1x3), \(PQ\) will be a 3x3 matrix:
\(PQ = \begin{bmatrix} -1 \times 2 & -1 \times -4 & -1 \times 1 \\ 2 \times 2 & 2 \times -4 & 2 \times 1 \\ 1 \times 2 & 1 \times -4 & 1 \times 1 \end{bmatrix}\)
Simplifying each element gives:
\(PQ = \begin{bmatrix} -2 & 4 & -1 \\ 4 & -8 & 2 \\ 2 & -4 & 1 \end{bmatrix}\)
Step 2: Transpose the matrix \(PQ\).
The transpose of a matrix is obtained by swapping its rows and columns, so \((PQ)^T\) is:
\((PQ)^T = \begin{bmatrix} -2 & 4 & 2 \\ 4 & -8 & -4 \\ -1 & 2 & 1 \end{bmatrix}\)
Therefore, the final result for \((PQ)^T\) is:
\(\begin{bmatrix} -2 & 4 & 2 \\ 4 & -8 & -4 \\ -1 & 2 & 1 \end{bmatrix}\)
Consider the following Linear Programming Problem $ P $: Minimize $ x_1 + 2x_2 $, subject to
$ 2x_1 + x_2 \leq 2 $,
$ x_1 + x_2 = 1 $,
$ x_1, x_2 \geq 0 $.
The optimal value of the problem $ P $ is equal to:
Let $D = \{(x, y) \in \mathbb{R}^2 : x > 0 \text{ and } y > 0\}$. If the following second-order linear partial differential equation
$y^2 \frac{\partial^2 u}{\partial x^2} - x^2 \frac{\partial^2 u}{\partial y^2} + y \frac{\partial u}{\partial y} = 0$ on $D$
is transformed to
$\left( \frac{\partial^2 u}{\partial \eta^2} - \frac{\partial^2 u}{\partial \xi^2} \right) + \left( \frac{\partial u}{\partial \eta} + \frac{\partial u}{\partial \xi} \right) \frac{1}{2\eta} + \left( \frac{\partial u}{\partial \eta} - \frac{\partial u}{\partial \xi} \right) \frac{1}{2\xi} = 0$ on $D$,
for some $a, b \in \mathbb{R}$, via the coordinate transform $\eta = \frac{x^2}{2}$ and $\xi = \frac{y^2}{2}$, then which one of the following is correct?
Let \( p_1<p_2 \) be the two fixed points of the function \( g(x) = e^x - 2 \), where \( x \in {R} \). For \( x_0 \in {R} \), let the sequence \( (x_n)_{n \geq 1} \) be generated by the fixed-point iteration \[ x_n = g(x_{n-1}), \quad n \geq 1. \] Which one of the following is/are correct?