Proving Linear Independence in a Subset of Trigonometric Functions

In summary, the conversation discusses a question in linear algebra about proving the linear independence of a subset S. The person is seeking help and mentions a similar question that involves integration of sin(px)sin(qx) between -pi and pi. They also mention that the lecturer may have shown that sin(px) and sin(qx) are orthogonal if p/=q. The conversation ends with a question about what would happen if the sum is multiplied by sin(nx) or cos(nx) and integrated.
  • #1
Auron87
12
0
I'm stuck on a question in linear algebra, it reads "Show that the subset S={cos mx, sin nx: m between 0 and infinity, n between 1 and infinity} is linearly independent.

I really just don't know where to start. I've seen a similar question which was just sin (nx) and the lecturer integrated sin(px)sin(qx) between -pi and pi but I just don't see why he did that or anything.

Any starting help would be much appreciated, thanks.
 
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  • #2
Auron87 said:
I really just don't know where to start. I've seen a similar question which was just sin (nx) and the lecturer integrated sin(px)sin(qx) between -pi and pi but I just don't see why he did that or anything.
My guess is he showed that sin(px) and sin(qx) are orthogonal if p/=q. If two nonzero vectors are orthogonal then they are linearly independent.
 
  • #3
The definition of "linearly independent", applied here would be that
[itex]a_0+ a_1cos(x)+ b_1sin(x)+ a_2cos(2x)+ b_2sin(2x)+ ...= 0[/itex] only when each [itex]a_i[/itex] and [itex]b_i[/itex] is 0. What would you get if you multiply that sum by sin(nx) or cos(nx), for all n, and integrate?
 

1. What is the linear independence problem?

The linear independence problem is a mathematical concept that deals with the relationship between vectors in a vector space. It asks whether a given set of vectors can be combined in a linear combination to equal the zero vector.

2. How do you determine if a set of vectors is linearly independent?

A set of vectors is linearly independent if no vector in the set can be written as a linear combination of the other vectors. This means that the only way to get a linear combination of the set to equal the zero vector is if all coefficients in the combination are equal to zero.

3. What is the importance of linear independence in linear algebra?

Linear independence is important in linear algebra because it allows us to determine if a set of vectors spans the entire vector space. It also helps us to find a basis for the vector space, which is useful in solving systems of linear equations and other applications.

4. What is the difference between linear independence and linear dependence?

Linear independence and linear dependence are opposite concepts. If a set of vectors is linearly independent, it means that no vector in the set can be written as a linear combination of the other vectors. On the other hand, if a set of vectors is linearly dependent, it means that at least one vector in the set can be written as a linear combination of the other vectors.

5. How does the number of vectors in a set affect linear independence?

The number of vectors in a set can affect linear independence in several ways. If the number of vectors is greater than the dimension of the vector space, then the set is always linearly dependent. If the number of vectors is equal to the dimension of the vector space, then the set is linearly independent if and only if the vectors are not all multiples of each other. If the number of vectors is less than the dimension of the vector space, then the set can be either linearly independent or linearly dependent, depending on the specific vectors in the set.

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