Linear Transformations: Solving (iii)

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Homework Help Overview

The discussion revolves around linear transformations, specifically focusing on the matrix representation of a linear transformation in different bases. The original poster presents a problem involving the transformation φ and its matrix M^{\mathcal C}_{\mathcal C} in the context of polynomial spaces.

Discussion Character

  • Mixed

Approaches and Questions Raised

  • Participants explore the correctness of the matrix representation of the transformation φ in the ordered basis C. There are attempts to clarify the relationship between the transformation and its eigenvectors, with some participants suggesting that the matrix should be diagonal.

Discussion Status

Some participants affirm the original poster's approach for part (iii) while others express concerns about the accuracy of the matrix provided for part (ii). There is an ongoing examination of the definitions and representations of the transformation in different bases, with multiple interpretations being discussed.

Contextual Notes

Participants note potential misunderstandings regarding the matrix representations and the requirements for demonstrating linear independence or spanning in the context of the problem. There is also mention of the need to clarify the basis used for the transformation.

Ted123
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Homework Statement



[PLAIN]http://img219.imageshack.us/img219/2950/linl.jpg

Homework Equations



The Attempt at a Solution



Is this how I do part (iii)?

From (ii) I get:

M^{\mathcal C}_{\mathcal C} (\phi) = \begin{bmatrix} 1 & 3 & 2 \\ 1 & -3 & 0 \\ 0 & 0 & 2 \end{bmatrix}

3(iii)

M^{\mathcal C}_{\mathcal C} (\phi) {\bf v} = {\bf w} where {\bf w} is the coordinate vector of \phi (v) with respect to \mathcal C and {\bf v} is the coordinate vector of v\in V .

{\bf v} = \begin{bmatrix} 1 \\ -3 \\ \pi \end{bmatrix}

So {\bf w} = \begin{bmatrix} 1 & 3 & 2 \\ 1 & -3 & 0 \\ 0 & 0 & 2 \end{bmatrix} \begin{bmatrix} 1 \\ -3 \\ \pi \end{bmatrix} = \begin{bmatrix} 2\pi -8 \\ 10 \\ 2\pi \end{bmatrix}
 
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Yes, that's the correct method.
 
Is the matrix M^C_C(phi) supposed to be the matrix of phi in the ordered basis C? If so, your matrix is incorrect; 1+x, 1-x, and 1+x^2 are eigenvectors of phi, with eigenvalues 1, 3, and 2, respectively. The matrix you are looking for is a diagonal matrix.

Your approach for (iii) is correct; simply multiply the matrix of phi in the basis C by the coordinate matrix v; that will give you the coordinate matrix of phi(v).
 
I concur. I get a different matrix for part (ii).
 
ns2675 said:
Is the matrix M^C_C(phi) supposed to be the matrix of phi in the ordered basis C? If so, your matrix is incorrect; 1+x, 1-x, and 1+x^2 are eigenvectors of phi, with eigenvalues 1, 3, and 2, respectively. The matrix you are looking for is a diagonal matrix.

Your approach for (iii) is correct; simply multiply the matrix of phi in the basis C by the coordinate matrix v; that will give you the coordinate matrix of phi(v).

Well this is my approach to the whole question:

Part (i)

\phi (1) = 2-x = 2(1) -1(x) + 0(x^2)

\phi (x) = -1 + 2x = -1(1) + 2(x) + 0(x^2)

\phi (x^2) = x + 2x^2 = 0(1) + 1(x) + 2(x^2)

M^{\mathcal B}_{\mathcal B}(\phi) = \begin{bmatrix} 2 & -1 & 0 \\ -1 & 2 & 1 \\ 0 & 0 & 2 \\ \end{bmatrix}

Part (ii)

Since {\mathcal C} has size 3 and \text{dim}(\mathbb{R}_2[x])=3 it is enough to show that \mathcal C} is either linearly independent or spans V . For completeness let's do both.

{\mathcal C} is linearly independent if

\alpha (1+x) + \beta (1-x) + \gamma (1+x^2) = 0 \Rightarrow \alpha = \beta = \gamma = 0

\alpha + \alpha x +\beta - \beta x + \gamma + \gamma x^2 = 0

\alpha + \beta + \gamma + (\alpha - \beta)x + \gamma x^2 = 0

Equate coefficients.

\alpha + \beta + \gamma = 0 (1)

\alpha - \beta = 0 \Rightarrow \alpha = \beta (2)

\gamma = 0 (3)

Subbing (2) and (3) in (1) gives 2\alpha = 0 \Rightarrow \alpha = 0 \Rightarrow \beta = 0 from (2).

Hence \alpha = \beta = \gamma = 0 and \mathcal C is linearly independent.

\mathcal C spans V if

a_1 (1+x) + a_2 (1-x) + a_3 (1+x^2) = b_1 + b_2 x + b_3 x^2

has at least one solution for every set of coefficients b_1,b_2,b_3

a_1 + a_2 + a_3 + (a_1 - a_2)x + a_3x^2 = b_1 + b_2 x + b_3 x^2

Equating coefficients yields the following system of equations (*):

a_1 + a_2 + a_3 = b_1

a_1 - a_2 = b_2

a_3 = b_3

Transforming the augmented matrix

\begin{bmatrix} 1 & 1 & 1 & 1 & 0 & 0 \\ 1 & -1 & 0 & 0 & 1 & 0 \\ 0 & 0 & 1 & 0 & 0 & 1 \\ \end{bmatrix}

into row echelon form we get

\begin{bmatrix} 1 & 0 & 0 & \frac{1}{2} & \frac{1}{2} & -\frac{1}{2} \\ 0 & 1 & 0 & \frac{1}{2} & -\frac{1}{2} & -\frac{1}{2} \\ 0 & 0 & 1 & 0 & 0 & 1 \\ \end{bmatrix}

which corresponds to the following system of equations:

a_1 = \frac{1}{2}b_1 + \frac{1}{2}b_2 -\frac{1}{2}b_3

a_2 = \frac{1}{2}b_1 -\frac{1}{2}b_2 -\frac{1}{2}b_3

a_3 = b_3

This system {and therefore the system (*)} are consistent for all RHS values, therefore \mathcal C spans V .

We can therefore conclude that \mathcal C is certainly a basis for V .

\phi (1+x) = (2-1) + (-1+2)x = 1 + x = 1(1) + 1(x) + 0(x^2)

\phi (1-x) = (2+1) + (-1-2)x = 3-3x = 3(1) - 3(x) + 0(x^2)

\phi (1+x^2) = 2 + (-1+1)x + 2x^2 = 2+2x^2 = 2(1) + 0(x) + 2(x^2)

M^{\mathcal C}_{\mathcal C} (\phi) = \begin{bmatrix} 1 & 3 & 2 \\ 1 & -3 & 0 \\ 0 & 0 & 2 \end{bmatrix}

Part (iii)

M^{\mathcal C}_{\mathcal C} (\phi) {\bf v} = {\bf w} where {\bf w} is the coordinate vector of \phi (v) with respect to \mathcal C and {\bf v} is the coordinate vector of v\in V .

{\bf v} = \begin{bmatrix} 1 \\ -3 \\ \pi \end{bmatrix}

So {\bf w} = \begin{bmatrix} 1 & 3 & 2 \\ 1 & -3 & 0 \\ 0 & 0 & 2 \end{bmatrix} \begin{bmatrix} 1 \\ -3 \\ \pi \end{bmatrix} = \begin{bmatrix} 2\pi -8 \\ 10 \\ 2\pi \end{bmatrix}
 
You don't need to do all of that work. For (i) (and (ii)) simply find the coordinate matrices of phi(1), phi(x) and phi(x^2) in the ordered basis B (or phi(1+x), phi(1-x), phi(1+x^2) in the ordered basis C). These coordinate matrices are, in order, the columns of the matrix you seek.

Now, for part (ii), to show that those three functions are a basis, it suffices to show that they are linearly independent. This is not difficult to do, and your way works fine.

If M^B_B(phi) is indeed meant to represent the matrix of phi in the ordered basis B, then I think your only mistake is that you are misunderstanding what this matrix is.
 
ns2675 said:
You don't need to do all of that work. For (i) (and (ii)) simply find the coordinate matrices of phi(1), phi(x) and phi(x^2) in the ordered basis B (or phi(1+x), phi(1-x), phi(1+x^2) in the ordered basis C). These coordinate matrices are, in order, the columns of the matrix you seek.

Now, for part (ii), to show that those three functions are a basis, it suffices to show that they are linearly independent. This is not difficult to do, and your way works fine.

If M^B_B(phi) is indeed meant to represent the matrix of phi in the ordered basis B, then I think your only mistake is that you are misunderstanding what this matrix is.

The matrix for (1) is definitely correct (I was told it was by the lecturer) so the method I am using is correct (and is what we were taught).

I know I only need to show EITHER linear independence OR span for part (ii) but for COMPLETENESS (and to make sure I could do both) I did BOTH!

[PLAIN]http://img832.imageshack.us/img832/1083/matrixtp.jpg

I've just noticed that I've wrote the images of the vectors in C as a linear combination of the vectors in B rather than C for part (ii)...
 
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Sorry, just realized you already wrote that; I was confusing the numbers on your question. Under part (i) I think you wrote something different on the solution from what was written in the problem; it seems as though part (i) of the problem is under part (ii) of your solution. Yes, you are exactly right.
 
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Just read your last post; that definition is what I was thinking of.

I didn't mean to reiterate that point about only needing to show independence; I see you already wrote that.

Hope I could help.
 
  • #10
ns2675 said:
The coordinate matrices for phi(1), phi(x), phi(x^2) in the ordered basis B be should be obtained as follows.

phi(1) = 2 - x = 2(1) - 1(x) + 0(x^2);
phi(x) = -1 + 2x = -1(1) + 2(x) + 0(x^2);
phi(x^2) = x + 2x^2 = 0(1) + 1(x) + 2(x^2).

(Wish I knew how to use Tex, for your sake!) From the above equations, you can read of the coordinates; those are the columns of your matrix. In fact, your matrix should be the transpose of the coefficient matrix of the above system of equations. Deal similarly with the ordered basis C (it's a bit easier; as I said before, the elements of C are each eigenvectors of phi).

I know - that's how I got the matrix for part (i)!

Sorry I just noticed I posted my working to a completely different question before...
 
  • #11
Ted123 said:
I've just noticed that I've wrote the images of the vectors in C as a linear combination of the vectors in B rather than C for part (ii)...
Yeah, that's your mistake.
 
  • #12
Sorry about that confusion, I just realized that.
 
  • #13
ns2675 said:
Just read your last post; that definition is what I was thinking of.

I didn't mean to reiterate that point about only needing to show independence; I see you already wrote that.

Hope I could help.

Sorry everyone!

Just to clarify I posted my working to a completely different question before and mixed up the numbering of the question parts in my working!

It seems my mistake for part (ii) is writing the images as a linear combination of vectors in B rather than C.
 
  • #14
vela said:
Yeah, that's your mistake.

So is this correct:

M^{\mathcal C}_{\mathcal C} (\phi) = \begin{bmatrix} 1 & 0 & 0 \\ 0 & 3 & 0 \\ 0 & 0 & 2 \end{bmatrix}

(And obviously then I've got to correct part (iii) )
 
  • #15
Yeah, that's the right matrix.
 

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