Is the Set of Functions f[sub k] a Basis for the Vector Space V?

In summary, we are given a set S and a field F, and we define a vector space V as the set of all functions from S to F where the function is equal to 0 for all but finitely many elements in S. We are asked to prove that the set {fk} with k from S is a basis for V. To do this, we need to show that {fk} spans any vector from V and is linearly independent. Using the definition of V, we can show that {fk} satisfies both of these conditions, thus proving that it is a basis for V.
  • #1
flyerpower
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Homework Statement


Let S be any non-empty set, F be a field and V={ f : S -> F such that f(x) = 0 } be a vector space over F.
Let f[sub k] (x) : S -> F such that f[sub k] (x) = 1 for k=x, otherwise f[sub k] (x) = 0.

Prove that the set { f [sub k] } with k from S is a basis for the vector space V.

The Attempt at a Solution



I tried to sketch something but i am not sure I'm on the right path.

So, given B={ f [sub k] }, k from S, it is a basis for V if and only if B spans any vector from V and B is linearly independent.

Let g : S -> F be a vector from V, then g(x)=0 and a some scalars from F with i >= 1.

Then B spans g if and only if g = sum ( a * f ).
But g(x) = 0 so 0 = sum ( a * f ), so the vectors f are linearly independent.

So i'd say B is a basis for the vector V, but I'm not sure it's correct because i didn't make use of the definition of the function f.
 
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  • #2
I am a little confused by your notation. Which is the correct V:
  • V = {f:S → F | f = 0}
  • V = {f:S → F | f(x0) = 0 for some x0 in S}
 
  • #3
jgens said:
I am a little confused by your notation. Which is the correct V:
  • V = {f:S → F | f = 0}
  • V = {f:S → F | f(x0) = 0 for some x0 in S}

It's not specified, so i guess it's f(x) = 0 for all x in S.
 
  • #4
I didn't think of this at first, but that seems to be problematic. For {fk} to be a basis, it needs to be a subset of V. But since V contains only the function that is 0 everywhere and fk is not the zero function, this is a contradiction.

Are you sure that's what is meant by V?
 
  • #5
This is what concerned me too.
Honestly i don't quite understand the definition of V as it doesn't say anything clear about x in f(x), but, actually i think V is defined such that f(x)=0 for a finite number of elements in S.
 
  • #6
I think I have it figured out. Use V = {f:S → F | f(x) = 0 for all but finitely many x}. Can you show that {fk} are a basis for V?
 
  • #7
Well, the definition of V doesn't change the situation, the problem is that i don't know the dimension of V, is it finite?
 
  • #8
The dimension of V does not matter. With this definition of V you can show that {fk} is a basis. And your proof earlier isn't quite right, so you'll need to improve that for this.
 
  • #9
Ok, thank you, i'll take one more ride :).
 
  • #10
I don't understand why V is the set of all functions such that f(x)=0 for a finite number of S.

For example if S={1,2}, does that mean that a vector in S is (f(1),f(2))? with f(1)=0, f(2)=b, with b in F. Or
f(1)=a, f(2)=b, with a,b in F.

The basis is {(f[sub 1](1),f[sub 1](2)),f[sub 2](1),f[sub 2](2))} = {(1,0),(0,1)}.
But i don't understand why f(x) must be 0 for some arbitrary points in S.
 
  • #11
You are confused because you are not reading things correctly. If you use V = {f:S → F | f(x) = 0 for all but finitely many x} then the {fk} constructed in the posts above are a basis for V.

As for your particular objection, note that if S is finite and f is non-zero everywhere, then f(x) = 0 except at a finite number of points.
 
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  • #12
You're right. I was confused because i thought f and f[sub k] are not the same functions. Now it makes sense, thank you.
 

FAQ: Is the Set of Functions f[sub k] a Basis for the Vector Space V?

1. What is a vector space basis?

A vector space basis is a set of vectors that can be used to represent any other vector in the vector space through linear combinations.

2. Why is it important to prove the existence of a vector space basis?

Proving the existence of a vector space basis is important because it ensures that the set of vectors chosen can accurately represent any vector in the vector space. This allows for efficient and accurate computations in linear algebra.

3. How is the existence of a vector space basis proven?

The existence of a vector space basis can be proven by showing that the set of vectors is linearly independent (no vector can be written as a linear combination of the other vectors) and spans the entire vector space (any vector in the space can be written as a linear combination of the set).

4. Can a vector space have more than one basis?

Yes, a vector space can have multiple bases. In fact, any two bases of a vector space will have the same number of vectors, known as the dimension of the vector space.

5. How is a vector space basis used in practical applications?

Vector space bases are used in practical applications to represent and manipulate data in linear algebra, such as in machine learning, computer graphics, and physics. They allow for efficient calculations and transformations of vectors in a given vector space.

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