Matrix of a linear transformation

In summary: M_{ED}(S) is the coordinate representation of the linear transformation S, with respect to the bases E and D.
  • #1
stunner5000pt
1,461
2
This is how the question appears in my textbook
Find the matrix of T corresponding to the bases B and D and use it to compute [itex] C_{D}[T(v)] [/itex] and hence T(v)

T; P2 - > R2
T(a + bx + cx^2) = (a+b,c)
B={1,x,x^2}
D={(1,-1),(1,1)}
v = a + bx + cx^2

ok i cna find Cd no problem it is
[tex] C_{D}[T(v)] = \frac{1}{2} \left(\begin{array}{ccc} 1&1&-1 \\ 1&1&1 \end{array}\right) [/tex]

now am i supposed to solve for X where
[tex] C_{D}[T(v)] X = T(v) [/tex]

but textbook doesn't do that...
it does [tex] C_{D}[T(v)] \left(\begin{array}{c} a \\ b \\ c \end{array}\right) = X [/tex]

It doesn't make sense... doesn't the question ask to compute Cd[T(v)] and T(v) from it??

Next question
Verify this theorem for the given transformation and uses the standard basis in Rn
Theorem:
[itex] M_{EB} (ST) = M_{ED} (S) \bullet M_{DB} (T) [/itex]

T;R3 -> R4
S: R4->R2
T(a,b,c) = (a+b,b+c,c+a,b-a)
S(a,b,c,d) = (a+b,c-d)

[tex] M_{EB} (S) = \left[C_{D}\left(\begin{array}{c} 1 \\ 0 \end{array}\right) \ C_{D}\left(\begin{array}{c} 1 \\ 0 \end{array}\right) \ C_{D}\left(\begin{array}{c} 0 \\ 1 \end{array}\right) \
C_{D}\left(\begin{array}{c} 0 \\ -1 \end{array}\right)\right] [/tex]
[tex] M_{EB} (S) = \left[\begin{array}{cc} 1&0 \\ 1&0 \\ 0&1 \\ 0&-1 \end{array}\right] [/tex]

[tex] M_{DB} (T) = \left[C_{D}\left(\begin{array}{c} 1 \\ 0 \\1 \\ -1 \end{array}\right) \ C_{D}\left(\begin{array}{c} 1 \\ 1 \\ 0 \\ 1 \end{array}\right) \ C_{D}\left(\begin{array}{c} 0 \\ 1 \\ 1 \\ 0 \end{array}\right)\right] [/tex]

[tex] M_{DB} (T) = \left[\begin{array}{cccc} 1&0&1&-1 \\ 1&1&0&1 \\ 0&1&1&0 \end{array}\right] [/tex]

the dimensions of the matrices are not correct though..

is there something wrong in the way i am forming the matrices?
 
Last edited:
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  • #2
What does [itex]C_D[T(v)][/itex] mean?

First off, did you notice that T(v) is a vector in R²?


I think it might help you a great deal to write down explicitly exactly what type everything is in your equations. E.G. you might write down:

v : element of P2
T : transformation from P2 --> R²
T(v) : element of R²
[itex]C_D[T(v)][/itex] : 2x1 matrix.


I'm going to assume [itex]C_D[w][/itex] means the coordinate representation of the vector w, with respect to the basis D.

So you didn't compute [itex]C_D[T(v)][/itex] at all -- instead, you computed [itex]M_{B,D}[T][/itex] which is the coordinate representation of the linear transformation T, with respect to the bases B and D!

You really ought to go reread the section on coordinates and bases. The whole point of coordinates is that they simply transform the equation into matrices. In other words, the equation:

T(v) = w

is true if and only if the equation

[tex]M_{B,D}[T] \cdot C_B[v] = C_D[w][/tex]

is true.
 
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  • #3
is there something wrong in the way i am forming the matrices?
Well, you're certainly not internally consistent:

[tex] M_{DB} (T) = \left[C_{D}\left(\begin{array}{c} 1 \\ 0 \\1 \\ -1 \end{array}\right) \ C_{D}\left(\begin{array}{c} 1 \\ 1 \\ 0 \\ 1 \end{array}\right) \ C_{D}\left(\begin{array}{c} 0 \\ 1 \\ 1 \\ 0 \end{array}\right)\right] [/tex]

First, you wrote down the matrix with three columns, each of which is supposed to be the coordinate representation of a vector in R^4.

[tex] M_{DB} (T) = \left[\begin{array}{cccc} 1&0&1&-1 \\ 1&1&0&1 \\ 0&1&1&0 \end{array}\right] [/tex]

And then you wrote down a matrix whose rows are the transpose of those coordinate representations.


Incidentally, based on how the problem's stated, E is the basis on R^4, and D is the basis on R³, so you meant [itex]M_{ED}(S)[/itex] and not [itex]M_{EB}(S)[/itex].
 
  • #4
Hurkyl said:
Well, you're certainly not internally consistent:



First, you wrote down the matrix with three columns, each of which is supposed to be the coordinate representation of a vector in R^4.



And then you wrote down a matrix whose rows are the transpose of those coordinate representations.


Incidentally, based on how the problem's stated, E is the basis on R^4, and D is the basis on R³, so you meant [itex]M_{ED}(S)[/itex] and not [itex]M_{EB}(S)[/itex].

well then what is the different between [itex] M_{ED}(s) [/itex] and [itex] M_{EB}(S) [/itex] is it even possible to form the former?
 

What is a matrix of a linear transformation?

A matrix of a linear transformation is a representation of a linear transformation between two vector spaces. It is a rectangular array of numbers that can be used to describe the transformation of one vector space into another.

How is a matrix of a linear transformation related to a linear transformation?

A matrix of a linear transformation is directly related to a linear transformation. It represents the same transformation in a different form. The matrix provides a more concise and efficient way to represent the transformation and allows for easier calculations.

How do you construct a matrix of a linear transformation?

To construct a matrix of a linear transformation, you first need to determine the basis of the input and output vector spaces. Then, the columns of the matrix will be the coordinates of the transformed basis vectors in the output space. The resulting matrix will have the same number of columns as the dimension of the output space and the same number of rows as the dimension of the input space.

What is the significance of a matrix of a linear transformation?

A matrix of a linear transformation is significant because it allows for the efficient representation and calculation of a linear transformation. It also provides insight into the properties of the transformation, such as whether it is invertible or has a determinant of zero.

Can a matrix of a linear transformation be used for more than two vector spaces?

Yes, a matrix of a linear transformation can be used for any number of vector spaces. Each column of the matrix will represent the coordinates of the transformed basis vectors in the corresponding output space. However, the dimensions of the input and output spaces must match in order for the transformation to be valid.

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