Basis of Image of Linear Transformation

In summary, the given linear transformation F maps a three-dimensional vector space to a one-dimensional vector space, with the vector (1) forming the basis for the image of F. Therefore, the dimension of the image of F is 1. This can also be seen by the fact that F(0,0,z) = z, making the image of F equal to all real numbers.
  • #1
lkh1986
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Homework Statement



Given a linear transformation F: R^3 --> R, F(x,y,z) = 3x-2y+z, find I am (F) and dim (Im (F))



Homework Equations



I have found that dim(ker F) = 2 and from the theorem dim (V) = dim (Ker F) + dim (Im F), I know dim (V) = 3, so dim (Im F) = 1.


The Attempt at a Solution



Im (F) = {F(x,y,z) | (x,y,z) inside R^3}
= (3x2y+z | x, y, z inside R}
= {R}
= L(1)

The vector (1) forms the basis for the image of F. Dim (Im F) = 1.

Is this the correct solution? It seems correct to me, since (1) is the standard basis for the vector space R.

Thanks.
 
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  • #2
Quite correct. You didn't even need to use the theorem. F(0,0,z)=z. It's pretty clear from that that Im(F)=R, right? And dim(R)=1.
 

FAQ: Basis of Image of Linear Transformation

What is the basis of an image in linear transformation?

The basis of an image in linear transformation refers to the set of vectors that span the range or output of the transformation. In other words, it is the set of vectors that the transformation maps the input vectors onto.

Why is the basis of an image important in linear transformation?

The basis of an image is important because it helps us understand the properties and behavior of the transformation. It can also be used to determine the dimension and rank of the transformation, which are important concepts in linear algebra.

How is the basis of an image related to the basis of the domain in linear transformation?

The basis of an image and the basis of the domain are closely related in linear transformation. The basis of the image is dependent on the basis of the domain, as it is the result of applying the transformation to the basis vectors of the domain.

Can the basis of an image change in different linear transformations?

Yes, the basis of an image can change in different linear transformations. This is because the basis vectors of the domain and the transformation itself can vary, resulting in different images and therefore different bases.

How can we find the basis of an image in linear transformation?

To find the basis of an image in linear transformation, we can apply the transformation to the basis vectors of the domain and then determine which vectors in the output are linearly independent. These linearly independent vectors form the basis of the image.

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