Finding image of linear transformation (difficult)

In summary, Micromass explains how to find the image of a linear transformation using a basis and solving for echelon form. He also points out that you can prove the image forms a subspace of a given space by showing that 0 is in the image for a given linear transformation and satisfying the scaler multiplication and axiom of extension.
  • #1
andrey21
476
0
1. Find the image of the linear transformation whose matrix is given by:

1 2 5 2
4 -3 1 0
10 -13 -7 -4


Homework Equations





3. Tried numerous times but struggle to get anywhere
 
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  • #2
Take a basis of the domain, preferably (1,0,0,0), (0,1,0,0), (0,0,1,0), (0,0,0,1). Then the image of this basis will span the image of the linear transformation (but it won't be a basis in general). You can use this to find the image of this transformation...
 
  • #3
Thanks micromass I sort of understand what u are saying could u possibly start me off with the calcuation.
 
  • #4
Take the basis element (1,0,0,0) and calculate it's image.
The image of a vector x under a matrix A is Ax. So it's just a matrix multiplication...
 
  • #5
So the taking the basis element (1,0,0,0):

T(1,0,0,0) = (1,4,10,0) ?
 
  • #6
No, T(1,0,0,0) = (1,4,10). I'm not sure how you found that zero in the end...
 
  • #7
Yep sorry I don't know why i put the extra zero in so:

T(1,0,0,0) = (1,4,10)
T(0,1,0,0) = (2,-3,-13)
T(0,0,1,0) = (5,1,-7)
T(0,0,0,1) = (2,0,-4)
Correct?
 
  • #8
Yes, correct :approve:

Now the set spanned by those four vectors will be your image.
 
  • #9
Ok sorry if seems dumb but the set spanned, what does this mean exactly?
 
  • #10
The set spanned by some vectors is the set of all linear combinations of these vectors.
 
  • #11
Im really confused how would this calcultion start?
 
  • #12
Setting Ax = 0 and solving to find echelon form:

1 2 5 2
0 11 19 8
0 0 0 0
 
  • #13
There are no calculations anymore. You already found the answer...
 
  • #14
So that is the image of the linear transform?
 
  • #15
The answer is just that the image is the set of all linear combinations of (1,4,10), (2,-3,-13), (5,1,-7) and (2,0,-4). Explicitly:

[tex]Image=\{\alpha(1,4,10)+\beta(2,-3,-13)+\gamma(5,1,-7)+\delta(2,0,-4)~\vert~\alpha,\beta,\gamma,\delta\in \mathbb{R}\}[/tex]

You can span the image with less then 4 vectors however, but this doesn't seem to be the question...
 
  • #16
Ah i see well the next part of the question goes on to say:

Give three vectprs which are in the image?
 
  • #17
Thats not to difficult is it? You've found four vectors which is in the image, so you've got three vectors to...
 
  • #18
Yes I understand now so I can just take 3 of the 4 vectors used. The final part of the question says show explicity that image forms a subspace. So i should just use vectors and make sure satisfy the axioms?
 
  • #19
Yeah, there are many ways to do this. But what you suggest seems good...
 
  • #20
Great Thanks for all ur help micromass :)
 
  • #21
Sorry micromass quick qustion as i have stated above i could use vectors to prove the image forms a subspace of R^3. How would I go about doing this, sub in vectors to the image?
 
  • #22
You could prove this in general. Let T:V--> W be a linear transformation, then im(T) is a subspace of W.
You'll only need to prove that
1) 0 in im(T)
2) v+w in im(T) whenever v,w in im(T)
3) av in im(T) whenever a in R and w in im(T).
 
  • #23
Ah I see so:

1) 0 in image(T) would that just be (0,0,0) ?
 
  • #24
Yes, I am sorry, with 0 I just meant (0,0,0)...
 
  • #25
Rite so showing (0,0,0 is in im(T) would just be a case of subbing that into the image? Say swappping (1,4,10) for (0,0,0) ?
 
  • #26
No. (0,0,0) is in the image because T(0,0,0,0)=(0,0,0).
 
  • #27
Yep I understand now. With the addition axiom shall I just add (1,0,0,0) and (0,1,0,0) for example. Therefore giving me a vector (3,1,-3) ?

And finally with the scaler multiplication axiom:

2.(1,0,0,0) = 2.(1,4,10) = (2,8,20) ?
 
  • #28
Is this correct micromass?
 
  • #29
Yes, I can see what you mean and it is correct.
However, I must also tell you to watch your notation: writing that 2.(1,0,0,0) = 2.(1,4,10) is not correct. You have to write 2.f(1,0,0,0) = 2.(1,4,10)...
 
  • #30
Oh why is the f there just out of curiosity?
 
  • #31
Oh, I am sorry, that f had to be a T :shy:
 
  • #32
Haha I see now, well again thanks for all ur help:)
 

FAQ: Finding image of linear transformation (difficult)

How do I find the image of a linear transformation?

To find the image of a linear transformation, you need to apply the transformation to each vector in the domain. This will result in a new set of vectors, which make up the image of the transformation.

What makes finding the image of a linear transformation difficult?

Finding the image of a linear transformation can be difficult because it involves understanding the concept of linear transformations and how they affect vectors in a given space. It also requires knowledge of matrix operations and linear algebra.

Can I use a calculator to find the image of a linear transformation?

Yes, you can use a calculator to find the image of a linear transformation. Many scientific and graphing calculators have built-in functions for performing matrix operations, which can make finding the image of a linear transformation easier.

What are some common mistakes when finding the image of a linear transformation?

Some common mistakes when finding the image of a linear transformation include not properly applying the transformation to each vector in the domain, not understanding the properties of linear transformations, and making errors in matrix operations.

How can I check if I have correctly found the image of a linear transformation?

You can check if you have correctly found the image of a linear transformation by verifying that the resulting vectors in the image satisfy the properties of a linear transformation. Additionally, you can compare your results with other methods or solutions to ensure accuracy.

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