Linear Transformation: Converting Between Canonical and Basis Representations

In summary, the matrix T in relation to the basis set B= {(-1, 1), (0, 1)} is true or false depending on whether or not the operator T(x,y) = (x, 3x+y) for all x,y∈ℝ.
  • #1
Victor Feitosa
15
0

Homework Statement



Being T: ℝ2 → ℝ2 the linear operator which matrix in relation to basis B = {(-1, 1), (0, 1)} IS:
[T]b =
\begin{bmatrix}
1 & 0\\
-3 & 1
\end{bmatrix}

True or False: T(x,y) = (x, 3x+y) for all x,y∈ℝ?

Homework Equations

The Attempt at a Solution

3
[/B]
So first I convert (x,y) from canonical to basis B and found (-1, 2).
Next, I calculate [T]b. (-1,2). Found that the result is (-x, 3x +2y).
Now, from my perspective i have to convert it to canonical basis again.
But how am I suposed to do it?
 
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  • #2
I am a little unclear of what the question is asking.
## [T]_b = \begin{bmatrix} 1&0\\-3&1 \end{bmatrix} ##
And in stacked matrix form:
## B = \begin{bmatrix} -1&0\\1&1 \end{bmatrix} ##
So, you are looking for a matrix A such that AB = [T]_b. Is that the correct understanding of the question?
 
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  • #3
Sorry, I just want to know if the following statement is true: True or False: T(x,y) = (x, 3x+y) for all x,y∈ℝ?
 
  • #4
##[T]_b## refers to the matrix operation conducted relative to the basis set B.
So if you start with (x,y) in the standard basis, what is (x,y) in basis B? ( y-x, y).
Then apply T_b to that and you will get T(x,y).
 
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  • #5
RUber said:
##[T]_b## refers to the matrix operation conducted relative to the basis set B.
So if you start with (x,y) in the standard basis, what is (x,y) in basis B? ( y-x, y).
Then apply T_b to that and you will get T(x,y).

I did what you said, but I get that T(x,y) = (-x+y, 3x-2y)
How I convert it to standard basis again?
I tried to multiply T(x,y).B , but my result is (4x -3y, 3x-2y)
I don't know what I am doing wrong..
 
  • #6
Victor Feitosa said:
I did what you said, but I get that T(x,y) = (-x+y, 3x-2y)
This looks right.
How I convert it to standard basis again?
You don't -- x and y are representative of the standard basis.
 
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  • #7
But the answer says that the statement T(x,y) = (x, 3x+y) for all x,y∈ℝ? is True.

Also, [T]b.(x,y)b return the answer in Basis B, not?
 
  • #8
Hmmm. Okay. So perhaps we did the operation backward to get from (x,y) in the standard basis to (a,b) in the basis B.
To point to ( x,y )_{x,y} you need a = -x, and b = x+y, or (-x, x+y)_B.
Hit that with T_b.
You get ( -x, 3x+x + y ) = (-x, 4x+y) in basis B.
Putting that back into the canonical basis, gives ( x , -x+4x+y).
Now I can see that the answer should be true.

The problem was that we were using the definition for basis vectors of B, as the operation to move from (x,y)_{x,y} to (a,b)_B, where really it is B * (a,b)_B = (x,y).
This means that:
(a,b)_B = B^{-1} (x,y).
T_b (a,b)_B = T_b B^{-1} (x,y), which as you said was in basis B.
So B T_b (a,b)_B =B T_b B^{-1} (x,y) will return the answer in the standard basis.

Sorry that took so long.
 
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  • #9
Since you are told what T is "in relation to basis B = {(-1, 1), (0, 1)}", write (x, y) in that basis:
(x, y)= a(-1, 1)+ b(0, 1)= (-a, a+ b) so we have -a= x and a+ b= y. a= -x so a+ b= -x+ b= y, b= x+ y.

(x, y)= -x(-1, 1)+ (x+ y)(0, 1). T(x, y)= -xT(-1, 1)+ (x+ y)T(0, 1).
 
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  • #10
Thank yu both, guys!
It took long to understand but thanks to you all I managed to grasp it. And I think it'll stick now!
 

Related to Linear Transformation: Converting Between Canonical and Basis Representations

1. What is a linear transformation?

A linear transformation is a mathematical function that maps one vector space to another in a way that preserves the basic structure of the original space. It is a fundamental concept in linear algebra and is used to describe many real-world phenomena.

2. How is a linear transformation different from other types of transformations?

A linear transformation is different from other types of transformations because it follows the rules of linearity, which include preserving addition and scalar multiplication. This means that the output of a linear transformation can be calculated by simply applying the transformation to each individual component of the input vector.

3. What are the applications of linear transformations?

Linear transformations have a wide range of applications in various fields such as physics, engineering, computer graphics, and economics. They are used to model and analyze systems, perform data compression and dimensionality reduction, and solve systems of linear equations.

4. How is a linear transformation represented mathematically?

A linear transformation can be represented mathematically using matrices and vectors. The transformation is applied by multiplying the input vector by a transformation matrix, which contains the coefficients for each component of the input vector. This results in a new vector that represents the transformed version of the original vector.

5. What is the difference between a linear transformation and a linear function?

A linear transformation is a broader concept that applies to vector spaces, while a linear function specifically refers to a transformation between real numbers. In other words, a linear function is a type of linear transformation, but not all linear transformations are linear functions.

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