Linear Transformation Matrix for T: U -> V using Standard Basis of R^2

In summary: Oh, I see what I did wrong. I accidentally added the components of the basis vectors instead of subtracting. The correct matrix for T would be:T(-1,1) = (-1-(-1),-1+1) = (0,0)T(0,-2) = (0-0,0+(-2)) = (0,-2)So the matrix for T would be:T = (0,0 0,-2)When multiplied by (a,b), this does indeed give (a-b,a+b) as the output.
  • #1
mathmathmad
50
0

Homework Statement


T : U -> V is a linear map defined by
T(a,b) = (a-b,a+b)
write down the matrix T using the standard basis of R^2

Homework Equations





The Attempt at a Solution


basis of V = { (1,1) , (-1,1) }

standard basis of R^2 is (1,0) and (0,1)
and the matrix T is essentially ( T(1,0) T(0,1) ) right? where T is a 2x2 matrix
but I don't know how to evaluate T(1,0) and T(0,1)...
 
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  • #2
mathmathmad said:

Homework Statement


T : U -> V is a linear map defined by
T(a,b) = (a-b,a+b)
write down the matrix T using the standard basis of R^2

Homework Equations





The Attempt at a Solution


basis of V = { (1,1) , (-1,1) }

standard basis of R^2 is (1,0) and (0,1)
and the matrix T is essentially ( T(1,0) T(0,1) ) right?[k/quote]
Yes, that is right.

where T is a 2x2 matrix
but I don't know how to evaluate T(1,0) and T(0,1)...
You are told how in the definition of T!
T(a,b) = (a-b,a+b)

so T(1, 0)= (1-0, 1+0) and T(0, 1)= (0-1, 0+1).
 
  • #3
oh yeah! oops

say if the basis given are (-1,1) and (0,-2)
what I get for matrix T is

T(-1,1) = (-1-1,-1+1) = (-2,0)
T(0,-2) = (0-(-2),0+(-2) = (2,-2)

so T is (-2, 0
2, -2 )

but when I multiply it with (a,b) to its RHS, I don't get (a-b,a+b)
 

1. What is a linear transformation?

A linear transformation is a mathematical function that maps a vector space to another vector space while preserving the basic algebraic structure of the space. In simpler terms, it is a transformation that can be represented by a matrix multiplication.

2. What are the properties of a linear transformation?

There are three main properties of a linear transformation:

  • Additivity: If f is a linear transformation, then f(x + y) = f(x) + f(y) for all vectors x and y.
  • Homogeneity: If f is a linear transformation, then f(cx) = c*f(x) for any scalar c and any vector x.
  • Preservation of zero: If f is a linear transformation, then f(0) = 0.

3. How is a linear transformation represented?

A linear transformation can be represented by a matrix. The columns of the matrix are the images of the basis vectors of the input vector space, and the rows of the matrix contain the coordinates of the images of the basis vectors of the output vector space.

4. What are some common applications of linear transformations?

Linear transformations are used in various fields, such as computer graphics, physics, and economics. They are also used in machine learning and data analysis, as they can help transform and simplify complex data sets.

5. How do you determine if a transformation is linear?

To determine if a transformation is linear, you can check if it satisfies the three properties mentioned earlier: additivity, homogeneity, and preservation of zero. If it satisfies all three properties, then it is a linear transformation.

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