Linear algebra - best approximation

In summary, the conversation discusses the concept of finding the best approximation (P) to a given function (F) using the inner product <f, g> over the interval [0, 1]. The distance between the function and its approximation was found to be 0, leading to the question of why this is true. The answer is that if the given function is a polynomial of the same degree as the vector space W, which is the set of linear combinations of the basis functions in S, then the approximation using these basis functions will be exact. However, if the given function is not in W, then the approximation will only be an approximation.
  • #1
twotaileddemon
260
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Hi... I have a quick question. I'm given V = ([0,1], <f,g> = interval from 0 to 1 of f(x)g(x)dx, S = {1, 2x-1}, W = lin(s), and P exists in W.

I was determining the best approximation (P) to a function (F). F was some polynomial (3x + 5) and when I did the work I got P to be the same polynomial. (I used projections of both parts of S with F and added them)

The distance between them, d(F,P) was obviously 0, but I was wondering why this was true? I mean.. why it HAD to be true even before I computed P.

Is it because W and F were polynomials of the same degree and p exists in W? Thanks for your help.
Any elaboration is great :) I just want to understand why certain functions already have the best approximation to what is given.
 
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  • #2
twotaileddemon said:
Hi... I have a quick question. I'm given V = ([0,1], <f,g> = interval from 0 to 1 of f(x)g(x)dx, S = {1, 2x-1}, W = lin(s), and P exists in W.

I was determining the best approximation (P) to a function (F). F was some polynomial (3x + 5) and when I did the work I got P to be the same polynomial. (I used projections of both parts of S with F and added them)

The distance between them, d(F,P) was obviously 0, but I was wondering why this was true? I mean.. why it HAD to be true even before I computed P.

Is it because W and F were polynomials of the same degree and p exists in W? Thanks for your help.
Any elaboration is great :) I just want to understand why certain functions already have the best approximation to what is given.
What you've written here is not at all clear. It would help me understand what you're trying to do if you can answer the following questions.

  1. What do you mean that V = [0, 1]? Is this just the interval 0 <= x <= 1? If so, why is it named?
  2. <f, g> is not an interval; it is an integral, namely [tex]\int_0^1 f(x)g(x)dx[/tex]
  3. What is S? It appears to be a basis with two functions in it.
  4. What is W? You show it as equal to lin(s). Do you mean that W is the set of all linear combinations of the vectors in S (not s)? It would be helpful if you said that.
  5. How did you calculate the distance from one function to another? I'm guessing that you should be using the inner product you are given.

If an arbitrary function f is in W (that is, f is a linear combination of the functions in S), then I think that an approximation using the functions in W will be exact. If, on the other hand, f is not in W (for example, f(x) = x2), then an approximation will be just that, an approximation.
 

FAQ: Linear algebra - best approximation

1. What is linear algebra and how is it used in best approximation?

Linear algebra is a branch of mathematics that deals with linear equations and their representations in vector spaces. It is used in best approximation to find the closest possible solution to a given problem using a linear combination of known values.

2. Why is best approximation important in scientific research?

Best approximation is important in scientific research because it allows us to make accurate predictions and estimations based on limited data. It also helps us to simplify complex problems and make them more manageable.

3. What are some common techniques used in best approximation?

Some common techniques used in best approximation include least squares method, orthogonal projection, and singular value decomposition. These techniques involve finding the closest match between a set of data points and a mathematical model.

4. Can linear algebra be used in fields other than mathematics?

Yes, linear algebra can be applied in various fields such as physics, engineering, economics, and computer science. It is a fundamental tool for solving problems that involve large amounts of data and complex systems.

5. How does best approximation differ from other methods of approximation?

Best approximation differs from other methods of approximation in that it aims to minimize the overall error between the actual data and the approximated solution. Other methods may focus on reducing error in specific areas or may use different mathematical techniques.

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