Matrix Multiplication and Linear Transformations

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The discussion centers on understanding matrix multiplication and its relation to linear transformations, specifically how matrix A represents a transformation with a partitioned structure. The confusion arises from the negative value in the matrix and how it affects the transformation of variables x1 and x2, while x3 remains unchanged. Participants clarify that the transformation involves a rotation in the x1-x2 plane, represented by matrix M, and that the partitioning of matrix A is crucial for understanding its operation. Ultimately, the key takeaway is that the action of the operator primarily affects x1 and x2, simplifying the problem. The conversation concludes with a sense of clarity regarding the matrix's function.
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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
A = \begin{pmatrix} M & \textbf{0} \\ \textbf{0} & 1 \end{pmatrix}

with
M = \begin{pmatrix} \frac{1}{\sqrt{2}} & -\frac{1}{\sqrt{2}} \\ \frac{1}{\sqrt{2}} & \frac{1}{\sqrt{2}} \end{pmatrix}

and consider the product
M = \begin{pmatrix} x_1 \\ x_2 \end{pmatrix}

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..

M = \begin{pmatrix} x_1 \\ x_2 \end{pmatrix}

Is x1 and x2 equal to m11 and m12?

Which multiplied by the matrix M = \left[\stackrel{1}{0}\right]
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
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}

where
y_1= \begin{pmatrix}x_1 \\ x_2\end{pmatrix}
and y_2= x_3.

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

\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}
 
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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