Is the representation of x as a linear combination of u, v, and w unique?

In summary, the conversation is discussing how to start and complete a proof regarding linearly independent vectors and their representation of a given vector. The goal is to prove the uniqueness of this representation using the definition of Span(u, v, w) and assuming the contrary.
  • #1
sana2476
33
0
I attempted the proof but I don't know how to complete it..

Let u,v,w be linearly independent vectors and x is in <u,v,w>. Then there are unique a,b,y such that x=au+bv+yw
 
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  • #2
sana2476 said:
I attempted the proof

Great, let's see what you've done.
 
  • #3
I'm having trouble starting it...if u could help me start it..then i can try to carry it from there
 
  • #4
Look at the definition of <u,v,w>. What does it mean for x to be in <u,v,w>, spelled out in terms of the definition?
For the uniqueness part, start by assuming that you can write x=au+bv+cw and x=du+ev+fw, then prove that a=d, b=e, c=f.
 
  • #5
ok...so if i start the proof by saying if x is in <u,v,w> then there exists d,e,f such that x=du+ev+fw and then if i take the difference, say: (a-d)u+(b-e)v+(c-f)w...would that be right approach?
 
  • #6
By definition, if x is in Span(u, v, w), then there are scalars a, b, and c such that x = au + bv + cw. (I changed letters on you, here.

You want to show that this representation is unique, so one way to do this is to assume the contrary--that the representation is not unique, meaning that there is at least one other way to represent x, say, as du + ev + fw.

Work with these two representations, and you should get a contradiction, which means that your assumption that the representation was not unique must have been incorrect, which gets you back to the representation being unique.
 

FAQ: Is the representation of x as a linear combination of u, v, and w unique?

1. What is linear independence?

Linear independence refers to a set of vectors in a vector space that cannot be expressed as a linear combination of one another.

2. How is linear independence determined?

Linear independence can be determined by performing a linear combination of the vectors and setting it equal to zero. If the only solution to this equation is when all coefficients are equal to zero, then the vectors are linearly independent.

3. Why is linear independence important in mathematics and science?

Linear independence is important because it allows us to understand the relationships between vectors and determine if they are truly distinct or if they can be reduced to a smaller set. This is crucial in many areas of mathematics and science, such as linear algebra, differential equations, and physics.

4. Can a set of linearly dependent vectors still span a vector space?

Yes, a set of linearly dependent vectors can still span a vector space. However, the span of these vectors will not be unique and there will be redundancies in the information they provide.

5. How does linear independence relate to the concept of basis vectors?

Linear independence is closely related to the concept of basis vectors. A set of linearly independent vectors can form a basis for a vector space, meaning that they can be used to represent any vector in that space. However, not all basis vectors are linearly independent.

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