Determine a basis for the image of F

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    Basis Image
In summary: There are no other vectors in P2(R), so those two pieces of P2(R) account for all of P2(R). The two dimensions added together is the dimension of P2(R), which is 3.
  • #1
victoranderson
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Hello I have a question about part (b)

Now I know that F(f)(x) = [##\frac{1}{2}a+\frac{5}{6}b+\frac{17}{12}c]+[-a-2b-4c]x+[b+\frac{7}{2}c]x^{2}+[\frac{-2}{3}b-\frac{7}{3}c]x^{3}##

so Kernel of F : F(f)(x) =0

=> ##\frac{1}{2}a+\frac{5}{6}b+\frac{17}{12}c=0##
##-a-2b-4c=0##
##b+\frac{7}{2}c=0##
##\frac{-2}{3}b-\frac{7}{3}c=0##

which gives a=3c,b=-7c/2
so the basis for the kernel of F is (3,-7/2,1)

I think it is correct.

After that I am confusing about the basis for the image of F

When I convert the system of equations into matrix form and use wolframalpha to solve it
there are basis for column space and basis for row space
I do not know which one is the one I am looking for.
I think it should not be using matrix to determine the basis for the image of F because it should be used in the latter part.
 
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  • #2
The basis you found for the kernel of F is correct.

To find a basis for the image, you might start by finding a set of vectors that span the image of F and then find the largest subset that's linearly independent.
 
  • #3
vela said:
The basis you found for the kernel of F is correct.

To find a basis for the image, you might start by finding a set of vectors that span the image of F and then find the largest subset that's linearly independent.

so the basis for the image is {##\frac{1}{2},\frac{5}{6},\frac{17}{12}##} and {##-1,-2,-4##}?

Another question.
Since F: P2(R) -> P3(R), the dim(F) is 3 or 4?
After doing this question I think dim(F) = 3, since dim(ker(F)) = 1 and dim(Im(F))=2
 
  • #4
victoranderson said:
so the basis for the image is {##\frac{1}{2},\frac{5}{6},\frac{17}{12}##} and {##-1,-2,-4##}?
No. For one thing, the elements in the image of F are four-dimensional. Your vectors are three-dimensional.

Another question.
Since F: P2(R) -> P3(R), the dim(F) is 3 or 4?
After doing this question I think dim(F) = 3, since dim(ker(F)) = 1 and dim(Im(F))=2
I don't know what you mean by "dim(F)".
 
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  • #5
vela said:
No. For one thing, the image of F is four-dimensional. Your vectors are three-dimensional.I don't know what you mean by "dim(F)".

That is my question.
How do we determine the basis for the image and the dimensions?
If you say the image of F is four-dimensional, then basis for the image of F can only be
span {(1/2,-1,0,0),(5/6,-2,1,-2/3),(17/12,-4,7/2,-7/3)} = span {(1/2,-1,0,0),(5/6,-2,1,-2/3)}
Is it correct now?Last time I thought dim(F) = dim(im(F))+ dim (ker(F))
Actually it is dim(P2(R)) = dim(im(F))+ dim (ker(F). I understand now.
 
  • #6
victoranderson said:
That is my question.
How do we determine the basis for the image and the dimensions?
If you say the image of F is four-dimensional, then basis for the image of F can only be
span {(1/2,-1,0,0),(5/6,-2,1,-2/3),(17/12,-4,7/2,-7/3)} = span {(1/2,-1,0,0),(5/6,-2,1,-2/3)}
Is it correct now?
Sorry, I misspoke earlier. The image of F isn't four-dimensional; it's a subspace of a four-dimensional space. My point was that the vectors in Im(F) should have four coordinates, not three, as you seemed to have inferred.

If you rewrite what you wrote earlier for F(f)(x) slightly, you get

F(f)(x) = a(1/2 + x) + b(5/6 - 2x + x2 - 2/3 x3) + c(17/12 - 4x + 7/2 x2 - 7/3 x3),

which you can interpret as a linear combination of three vectors. Hopefully, that's what you did to come up with the vectors above.

The vectors (1/2,-1,0,0) and (5/6,-2,1,-2/3) are linearly independent and span the image, so they are a basis for Im(F). There are two vectors, so the dimension of the image is 2.


Last time I thought dim(F) = dim(im(F))+ dim (ker(F))
Actually it is dim(P2(R)) = dim(im(F))+ dim (ker(F). I understand now.
Right. When you talk about dimensions, you're talking about the dimension of a vector space (or subspace). To ask what dim(F) is doesn't make sense because F is a mapping, not a vector space, and as you noted, the domain and codomain have different dimensions.

The relation dim(P2(R)) = dim(im(F))+ dim(ker(F)) reflects the fact that you can split the domain into two pieces. The vectors in one piece, ker(F), all map to 0. The vectors in the other piece map onto the image of F.
 
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FAQ: Determine a basis for the image of F

What is the image of F?

The image of F is the set of all possible outputs or values produced by the function F when given a set of inputs.

How do you determine a basis for the image of F?

To determine a basis for the image of F, you can use the range space method or the column space method. The range space method involves finding the linearly independent columns of the matrix representing the function, while the column space method involves finding the columns of the matrix that have a pivot in the reduced row echelon form. Either method will give you a basis for the image of F.

Why is it important to determine a basis for the image of F?

Determining a basis for the image of F is important because it helps us understand the structure and range of the function. It also allows us to find a set of vectors that span the image of F, making it easier to perform calculations and solve problems related to the function.

Can the basis for the image of F be unique?

Yes, the basis for the image of F can be unique. This means that there is only one possible set of linearly independent vectors that span the image of F. However, in some cases, there may be multiple bases for the image of F, all of which are valid.

Are there any limitations to determining a basis for the image of F?

Yes, there are limitations to determining a basis for the image of F. For example, if the function F is not linear, it may not have a well-defined image and therefore a basis cannot be determined. Additionally, if the function has an infinite number of inputs and outputs, it may not be possible to determine a basis for the image of F.

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