Linear Transformations and Bases

In summary, when specifying a linear transformation, the basis in which it is described is not always specified. However, if no basis is mentioned, then the standard bases of Euclidean space are assumed.
  • #1
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I need some help or at least some assurance that my thinking on linear transformations and their matrix representations is correct.

I assume when we specify a linear transformation eg F(x,y, z) = (3x +y, y+z, 2x-3z) for example, that this is specified by its action on the variables and is not with respect to any basis.

However when we specify the matrix of a linear transformation T: V --> W that this is with respect to a basis in V and a basis in W

Of course if we have a linear transformation S: V -->V it could be that the two bases are the same.

If no basis is mentioned regarding the matrix of a linear transformation, then I am assuming the standard bases are assumed.

Can someone either confirm I am correct in my thinking or point out the errors in my thinking?

Peter
 
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  • #2
If no basis is mentioned regarding the matrix of a linear transformation, then I am assuming the standard bases are assumed.

What is the standard basis of a generic vector space V?
 
  • #3
Yes, good point ... I guess I should have specified Euclidean space for that assumption to make sense ...

Are my other assumptions/interpretations OK?
 
  • #4
Everything is correct, but I think you have a bit of a hangup on how linear transformations on vector spaces are described

I assume when we specify a linear transformation eg F(x,y, z) = (3x +y, y+z, 2x-3z) for example, that this is specified by its action on the variables and is not with respect to any basis.

However when we specify the matrix of a linear transformation T: V --> W that this is with respect to a basis in V and a basis in W

The key here is that in your first example you specified a linear transformation on R3 without defining it as a matrix multiplication, so no basis is required and no matrix is ever constructed. If you wanted to define F as a matrix multiplication you would need to specify a basis of R3 - on Euclidean space this step is often omitted because everyone assumes your basis is the standard basis (1,0,0),(0,1,0),(0,0,1) (and trying to specify F as matrix multiplication with respect to a different basis is literally just extra work).

If we want to specify a linear transformation V--> W as a matrix multiplication we need to pick bases of V and W to identify them with Euclidean space. But we can have linear transformations that are not represented as matrix multiplications. For example let V be the set of all polynomials of degree <= 3 (this is a 4 dimensional vector space over R) and let W be R. Then consider
[tex] I:V\to \mathbb{R},\ I(p(x)) = \int_0^1 p(x) dx [/tex]
I is a linear transformation and I never specified a basis for V in order to tell you the function because I didn't tell you what I was as a matrix multiplication
 
  • #5
Thanks so much for that post - most helpful

I suppose the essential thing needed to be able to derive a matrix of a linear transformation is that the vector spaces involved need to be over a field F where F = R or C.

Is that correct?

Missed your example due to some latex error or other - pity - would have like to have viewed your example

Thanks again!

Peter
 

Related to Linear Transformations and Bases

1. What is a linear transformation?

A linear transformation is a function that maps one vector space to another, while preserving the structure of the vector space. It follows two main properties: additivity and homogeneity.

2. How are linear transformations represented?

Linear transformations can be represented using matrices. Each column of the matrix represents the transformation of a basis vector in the original vector space.

3. What is a basis in linear algebra?

A basis is a set of linearly independent vectors that can be used to represent any vector in a vector space. It serves as a coordinate system for the vector space.

4. Can a linear transformation change the dimension of a vector space?

Yes, a linear transformation can change the dimension of a vector space. For example, a 2D vector space can be transformed into a 3D vector space through a linear transformation.

5. How do I determine the matrix representation of a linear transformation?

To determine the matrix representation of a linear transformation, you would need to apply the transformation to each basis vector in the original vector space and record the result. These results will then form the columns of the matrix representation.

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