Standard Matrix for an orthogonal projection transformation

In summary, the standard matrix for a linear transformation that projects an R^2 vector onto (-2, 4) is given by: \begin{bmatrix}-2 & 4 \\ -2 & -4\end{bmatrix}
  • #1
jmarzouq
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Let T:R^2 -> R^2 be the linear transformation that projects an R^2 vector (x,y) orthogonally onto (-2,4). Find the standard matrix for T.

I understand how to find a standard transformation matrix, I just don't really know what it's asking for. Is the transformation just (x-2, y+4)? Any clarification would be greatly appreciated, thanks! Also, sorry for the formatting, I'm on my phone.
 
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  • #2
Can you define an orthogonal projection? If (-2, 4) is in the range, what would a vector of its null space look like?
 
  • #3
You can do this pretty much by "brute strength". Since these vectors are in R2, your matrix is 2 by 2 and looks like
[tex]\begin{bmatrix}a & b \\ c & d\end{bmatrix}[/tex]
and, because this is a projection onto [-2, 4], maps [-2, 4] to itself:
[tex]\begin{bmatrix}a & b \\ c & d\end{bmatrix}\begin{bmatrix}-2 \\ 4\end{bmatrix}= \begin{bmatrix}-2a+ 4b \\ -2c+ 4d\end{bmatrix}= \begin{bmatrix}-2 \\ 4\end{bmatrix}[/tex]
so that -2a+ 4b= -2 and -2c+ 4p= 4. We can immediately divide by 2 to get -a+ 2b= -1 and -c+ 2d= 2.

Also, because this is an orthogonal projection, [4, 2], perpendicular to [-2, 4], must be mapped to 0.
[tex]\begin{bmatrix}a & b \\ c & d\end{bmatrix}\begin{bmatrix}4 \\ 2\end{bmatrix}= \begin{bmatrix}4a+ 2b \\ 4a+ 2d\end{bmatrix}= \begin{bmatrix}0 \\ 0 \end{bmatrix}[/tex]
so 4a+ 2b= 0 and 4c+ 2d= 0. We can again divide by 2 to get 2a+ b= 0 and 2c+ d= 0.

Solve the four equations -a+ 2b= -1, -c+ 2d= 2, 2a+ b= 0, and 2c+ d= 0 for a, b, c, and d.
 
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  • #4
Let's let [itex]v[/itex] be the normalised version of your vector (ie, divide your vector by its norm.) Now, if you have some vector [itex]w[/itex] and you want the projection onto [itex]v[/itex] then (as you probably know) this is just equal to [itex](v^\top w)v[/itex] (since the norm of [itex]v[/itex] is 1.) But this is equal to [itex]v(v^\top w)=(vv^\top)w[/itex]. Now, from this can you figure out how to form the projection?
 

FAQ: Standard Matrix for an orthogonal projection transformation

1. What is a standard matrix for an orthogonal projection transformation?

A standard matrix for an orthogonal projection transformation is a square matrix that represents an orthogonal projection transformation in a particular coordinate system. It is used to transform vectors from one coordinate system to another, preserving the angle between the vectors.

2. How is a standard matrix for an orthogonal projection transformation calculated?

A standard matrix for an orthogonal projection transformation can be calculated by first determining the basis vectors of the projection plane, which are orthogonal to each other. These basis vectors are then used to construct a matrix that represents the projection transformation.

3. What properties does a standard matrix for an orthogonal projection transformation have?

A standard matrix for an orthogonal projection transformation is a symmetric matrix, meaning that it is equal to its transpose. It is also idempotent, which means that when multiplied by itself, it results in the same matrix.

4. How is a standard matrix for an orthogonal projection transformation used in practical applications?

In practical applications, a standard matrix for an orthogonal projection transformation is used to project high-dimensional data onto a lower-dimensional space, while preserving the relationships between the data points. This is often used in data compression and dimensionality reduction techniques.

5. What are some examples of when a standard matrix for an orthogonal projection transformation is used?

One example of when a standard matrix for an orthogonal projection transformation is used is in computer graphics, where it is used to project 3D objects onto a 2D screen. It is also used in machine learning algorithms, such as Principal Component Analysis, to reduce the dimensionality of data sets.

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