Approximating function by trigonometric polynomial

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The discussion centers on approximating a function f(x) over the interval [0, π/2] using a trigonometric polynomial and a modified inner product. The best approximation theorem suggests that the truncated Fourier series provides the optimal approximation in a standard function space, but the challenge arises when using non-orthonormal basis functions like e^{inx}. The participants explore the implications of minimizing the expression (f-g, f-g) to find the best approximation, noting that the linearity of the inner product complicates the search for extrema. They conclude that the optimal coefficients a_n must be determined to minimize the nonlinearity introduced by the approximation. The conversation highlights the complexities of function approximation in restricted intervals and the need for careful analysis of the inner product properties.
ekkilop
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Hi!

Say that we wish to approximate a function f(x), \, x\in [0, 2\pi] by a trigonometric polynomial such that

f(x) \approx \sum_{|n|\leq N} a_n e^{inx} \qquad (1)

The best approximation theorem says that in a function space equipped with the inner product

(f,g) = \frac{1}{2 \pi} \int_0^{2\pi} f \bar{g} dx

the best possible approximation is the truncated Fourier series of the function, which follows from the orthonormality of the basis functions \{ e^{inx} \}. But what happens if we wish to consider a smaller interval, say x \in [0, \pi/2], and a corresponding inner product

(f,g) = \frac{2}{\pi} \int_0^{\pi/2} f \bar{g} dx

but still use the functions \{ e^{inx} \} (no longer orthonormal) in our approximation (1)? We could of course use the Fourier coefficients for all n that are multiples of 4 and set the rest to zero to get the corresponding Fourier series, but this is no longer the best possible approximation. So my question is basically, what would the best approximation be in this case?

Thank you!
 
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$$\frac{\partial (f,g)}{\partial a_n} = 0$$ for all ##a_n## is a natural result of an optimal solution. Analyzing this equation could give some interesting results.
 
Thank you mfb for your reply!

Yes, that was my original idea as well. If g is the approximation in the RHS of (1), then I reasoned that the optimal result should be when (f-g) \perp f. However, (f-g, f) is a linear function in the coefficients a_n so there are no extrema (I am assuming the coefficients are independent of x). Or perhaps I misunderstood something?
 
Ah, small fix:
I would expect that you want to minimize (f-g,f-g). As the inner product is linear in its arguments, (f-g,f-g) = (f,f) + (g,g) - (f,g) - (g,f) = (f,f) + (g,g) - 2 Re (f,g)
(f,f) is fixed, the other two parts depend on an and the expression should be minimal with respect to all an. The (g,g) part gives a nonlinearity with a proper minimum.
 
We all know the definition of n-dimensional topological manifold uses open sets and homeomorphisms onto the image as open set in ##\mathbb R^n##. It should be possible to reformulate the definition of n-dimensional topological manifold using closed sets on the manifold's topology and on ##\mathbb R^n## ? I'm positive for this. Perhaps the definition of smooth manifold would be problematic, though.

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