Linear algebra with proofs/vector space

In summary, the conversation discusses how to determine if a set of continuous real-valued functions, denoted as S, is a vector space over R by checking all the axioms. The individual steps for checking each axiom are outlined, starting with verifying (VS1) and considering the vectors as f(x), f(y), etc. The conversation also mentions being confused on how to proceed with the task.
  • #1
relskid
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Homework Statement



Suppose S denotes the set of continuous real-valued functions of a single variable f(x) having the property that f(x)=0 if |x|≥ 1. Show that S is a vector space over R by explicitly checking all the axioms.


Homework Equations



(VS1) For all x, y in V, x+y=y+x
(VS2) For all x, y, z in V, (x+y)+z=x+(y+z)
(VS3) There exists an element in V denoted by 0 such that x+0=x for each x in V
(VS4) For each element x in V there exists an element y in V such that x+y=0
(VS5) For each element x in V, 1x=x
(VS6) For each pair of elements a, b in F and each element x in V, (ab)x=a(bx)
(VS7) For each element a in F and each pair of elements x, y in V, a(x+y)=ax+ay
(VS8) For each pair of elements a, b in F and each element x in V, (a+b)x=ax+bx


The Attempt at a Solution



no real attempt yet. i am very lost on what i am supposed to do. all i really know is that I'm supposed to test S for each of those VS rules, and if they satisfy all of them, then S is a vector space over R. I'm just confused on how i am supposed to go about it.
 
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  • #2
Well, your vector space is S and your vectors are f(x),f(y),... so if (VS1) holds for S, then f(x)+f(y)=f(y)+f(x) which is clearly true for all real valued functions... do f(x),f(y)... satisfy VS2,VS3,...?
 

1. What is a vector space?

A vector space is a mathematical structure that consists of a set of vectors and a set of operations (addition and scalar multiplication) that can be applied to those vectors. This structure follows a set of properties, such as closure, associativity, commutativity, and distributivity, which allow for the manipulation and combination of vectors.

2. What are the basic properties of a vector space?

The basic properties of a vector space include closure (the result of any operation on vectors is still a vector within the space), associativity (the order of operations does not matter), commutativity (the order of vectors does not matter), and distributivity (the ability to distribute scalar multiplication over vector addition).

3. How do you prove that a set of vectors form a vector space?

To prove that a set of vectors form a vector space, you must show that the set follows all the properties of a vector space. This includes closure, associativity, commutativity, and distributivity. You must also show that the set contains a zero vector (a vector that, when added to any other vector, results in that vector) and that each vector has an additive inverse (a vector that, when added to the original vector, results in the zero vector).

4. What is a basis of a vector space?

A basis of a vector space is a set of linearly independent vectors that can be used to represent any vector within the space. This means that any vector within the space can be written as a unique linear combination of the basis vectors. The number of basis vectors is known as the dimension of the vector space.

5. What is the difference between a vector space and a subspace?

A vector space is a mathematical structure that contains a set of vectors and operations that can be applied to those vectors. A subspace, on the other hand, is a subset of a vector space that also follows the properties of a vector space. This means that all the vectors within a subspace must also be contained within the larger vector space and must follow the same properties.

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