Fourier transform of a functional

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Discussion Overview

The discussion revolves around the Fourier transform of a function defined on the interval (0,1), particularly focusing on the implications of boundary conditions and the potential for expressing transforms of higher powers or functionals of the original function in terms of its Fourier coefficients.

Discussion Character

  • Exploratory
  • Mathematical reasoning
  • Technical explanation

Main Points Raised

  • One participant inquires about the Fourier transform of a function x(s) and its derivatives, suggesting a relationship between the Fourier coefficients a_p and the transforms of higher powers of x.
  • Another participant suggests integrating by parts and notes that a Fourier series includes sine terms, although the original poster aims to avoid these due to boundary conditions.
  • The original poster expresses uncertainty about how integration by parts can relate back to the Fourier coefficients a_p when attempting to compute the transform of x^2.
  • One participant mentions that integrating by parts again could yield a second derivative and a cosine term, implying a potential pathway for further exploration.
  • A later reply introduces the concept that the Fourier transform of a product of functions is the convolution of their respective transforms, which may relate to the original poster's interest in functionals of x.

Areas of Agreement / Disagreement

Participants express differing views on the approach to take for integrating by parts and the implications of boundary conditions. There is no consensus on how to express the Fourier transform of higher powers of x or functionals of x in terms of a_p.

Contextual Notes

The discussion includes assumptions about the smoothness and differentiability of the function x(s), as well as the implications of boundary conditions on the Fourier series representation. The mathematical steps involved in the integration by parts are not fully resolved, leaving open questions about the relationships between the transforms.

Irid
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Hello,
I was wondering if such a thing even exists, so here it goes... Let's say I have a function x(s) (it is real, smooth, differentiable, etc.) defined on (0,1). In addition, dx/ds = 0 on the boundary (s=0 and s=1). I can compute its Fourier transform (?) as
a_p = \int_0^1 x(s) \cos(sp\pi)\, ds
and now I have a set of numbers a_p which contain the same information as the original function x(s).

The good news is that if I compute the same Fourier transform on the derivatives of x, i.e.
\int_0^1 \frac{d^2 x}{ds^2} \cos(sp\pi)\, ds = -p^2 \pi^2 a_p
I get an answer in terms of the a_p which I already know.

So here's my question:

What if I want to find the Fourier transform of higher powers of x?

\int_0^1 x^2 \cos(sp\pi)\, ds =\, ?

Can it be expressed in terms of, let's say, a power series in a_p?

\int_0^1 x^2 \cos(sp\pi)\, ds =\, ?\, \sum_{n=0}^{\infty} c_n a_p^n

And what if I want to find the Fourier transform of a generic functional f[x(s)] (smooth, differentiable, etc.)? Is it related somehow to the Fourier transform of the original function x(s)?
 
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Have you tried integrating by parts? Note that a Fourier series has sine terms as well as cosine.
 
mathman said:
Have you tried integrating by parts? Note that a Fourier series has sine terms as well as cosine.

Well I'm trying to keep things simple here by requiring dx/ds = 0 at the boundaries, hence all the sine terms are zero.

I don't know what to make of the integration by parts. Here's what I get

\int_0^1 x^2 cos(ps\pi)\, ds = -2\int_0^1 x\frac{dx}{ds}\sin(ps\pi)\, ds

I don't see how can this bring me back to the a_p...
 
I am not sure where you are going. However if you integrate by parts again you will get the second derivative and a cos.
 
I'm trying to solve a non-linear stochastic PDE of the type
dx/dt = d2x/ds2 + F[x] + noise(t)

and I would really benefit if it could be done with the Fourier transform because then I only need the first few terms of the Fourier expansion to have enough information about the x(s).. of course, all of this is to be done numerically
 
Irid,

I'm not sure if this helps, but... the Fourier transform of a product ##f(x)g(x)## is the convolution of their respective FTs.
 

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