Matrix Multiplication and Linear Transformations

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Homework Help Overview

The discussion revolves around matrix multiplication and its role in representing linear transformations. Participants are exploring how a specific matrix A relates to the transformation of vectors in a three-dimensional space, particularly focusing on the behavior of its components and the implications of partitioning the matrix.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning, Problem interpretation

Approaches and Questions Raised

  • Participants discuss the representation of matrix A as a linear transformation and question how specific elements affect the transformation. There are attempts to relate the matrix to its action on vectors, with some participants expressing confusion about the implications of negative elements and the partitioning of the matrix.

Discussion Status

Some participants have offered clarifications regarding the structure of the matrix and its components, while others are still grappling with the concepts. There is a recognition that the partitioning of the matrix is significant, particularly since one component remains unchanged during the transformation. The discussion is ongoing, with varying levels of understanding among participants.

Contextual Notes

There is an indication that participants are working under constraints typical of homework problems, such as needing to understand the implications of matrix operations without external resources. Some participants express frustration with their current understanding of matrices.

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Homework Statement



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Homework Equations



The Attempt at a Solution



I'm completely lost on this one.

I think the question is saying matrix A is a representation of a linear transformation, with the a11 and a21 transforming to a31, and so on for the other two columns. But I don't see how you can get that result with a12 being negative. This is all I could come up with after days of looking at this problem, and I'm just going around in circles :frown:

As for the product C=BA well that's pretty straightforward.

If someone can point me in the right direction it will be very much appreciated!
 
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so consider A as something like
[tex]A = \begin{pmatrix} M & \textbf{0} \\ \textbf{0} & 1 \end{pmatrix}[/tex]

with
[tex]M = \begin{pmatrix} \frac{1}{\sqrt{2}} & -\frac{1}{\sqrt{2}} \\ \frac{1}{\sqrt{2}} & \frac{1}{\sqrt{2}} \end{pmatrix}[/tex]

and consider the product
[tex]M = \begin{pmatrix} x_1 \\ x_2 \end{pmatrix}[/tex]

now relate that back to the original matrix A and its operation on and arbitrary x1,x2 and x3
 
So when you say the product..

[tex]M = \begin{pmatrix} x_1 \\ x_2 \end{pmatrix}[/tex]

Is x1 and x2 equal to m11 and m12?

Which multiplied by the matrix M = [itex]\left[\stackrel{1}{0}\right][/itex]
Edit:- I'm still not getting it. Matrices aren't making a lot of sense to me right now :(
 
Last edited:
I think lanedance spoke wrong in the last part of his response. I am sure he meant to say
[tex]A\begin{pmatrix}x_1 \\ x_2\\ x_3\end{pmatrix}= \begin{pmatrix}M & 0 \\ 0 & 1\end{pmatrix}\begin{pmatrix}y_1\\ y_2\end{pmatrix}[/tex]

where
[tex]y_1= \begin{pmatrix}x_1 \\ x_2\end{pmatrix}[/tex]
and [itex]y_2= x_3[/itex].

Of course, M is now a rotation matrix.
 
yeah thanks Halls, i didn't mean to have that last equals sign
 
Ok.. So for A * (x1,x1,x3), x1,x2 are mapped to new points, and x3 remains at the same point. Or with A partitioned to the 2x2 matrix M, and M * (x1,x2) + (0,0,x3) * A, you get exactly the same result right..

Is the partitioning completely arbitrary? I think that's what has been confusing me this whole time
 
T(x1,x2,x3)=A(x1,x2),x3

[tex]\begin{pmatrix} \frac{1}{\sqrt{2}} & -\frac{1}{\sqrt{2}} \\ \frac{1}{\sqrt{2}} & \frac{1}{\sqrt{2}} \end{pmatrix}\begin{pmatrix} x_1 \\ x_2 \end{pmatrix}[/tex]
 
The only reason to look at the partitioning is that x3 is unchanged by the operation in this problem.

So to understand the action of the operator we only need to consider its action on x1 and x2, which is a rotation in that plane, hence why we consider the partitioned matrix.
 
Ah.. I think it finally makes sense to me now. Thank you!
 
  • #10
no worries ;)
 

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