Fourier Basis functions question

In summary, the continuous Fourier Transform is often defined on a finite interval and can be used to create an orthonormal basis for L^2([-\pi,\pi]). However, when trying to compute the FT of a function on the whole \mathcal{R}, the basis functions have infinite 2-norm and are not square integrable. Therefore, they cannot form an orthonormal basis for L^2(\mathcal{R}). It is possible to expand functions in an unnormalised basis, but it is not possible to define an orthonormal basis for L^2(\mathcal{R}) with the Fourier basis.
  • #1
mnb96
715
5
Hi,
the continuous Fourier Transform is often defined on a finite interval, usually [tex][-\pi,\pi][/tex]:

[tex]\hat{f_k} = \frac{1}{2\pi}\int_{-\pi}^{\pi}f(x)e^{-ikx}dx[/tex]

If I understood correctly, this allows the basis functions to be defined so that they have norm=1, and they form an orthonormal basis for [tex]L^2([-\pi,\pi])[/tex].
Now, I get confused when one tries to compute the FT of a function f in the whole [tex]\mathcal{R}[/tex] because:

1) The 2-norm of the basis functions goes to [tex]+\infty[/tex]
2) They are not square integrable
3) Should I conclude that the basis-functions are orthogonal but NOT orthonormal?
4) If (1,2,3) are correct, then what is the space spanned by the basis-functions?
5) Is it possible to define an orthonormal basis for [tex]L^2(\mathcal{R})[/tex] with Fourier basis ?
 
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  • #2
I'm not familiar with a 2-norm but the basis is normalised "in my book" like so:

[tex]\int_{-\pi}^{\pi}\phi_{k}^{*}\phi_{k}dx = \frac{1}{2\pi}\int_{-\pi}^{\pi}e^{+ikx}e^{-ikx}dx = \frac{1}{2\pi}\int_{-\pi}^{\pi}dx = 1 [/tex]

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  • #3
Maybe I used an incorrect term, but indeed, you proved that the squared norm of the basis-functions are always 1.
The important points of my question (1,2,3,4,5) arise when the bounds of the integral are not anymore [tex][-\pi,\pi][/tex] but they become [tex](-\infty,+\infty)[/tex]

Basically, I wanted you to consider:
[tex]\int_{-\infty}^{+\infty}\phi_{k}^{*}\phi_{k}dx[/tex]
and then, answer those questions.
 
  • #4
I see what you mean now. In this case, I think you cannot define the basis.
But maybe there is a way to expand functions in an unnormalised basis.

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What are Fourier Basis functions?

Fourier Basis functions are a set of mathematical functions used to represent complex signals or data as a combination of simpler sinusoidal functions. They are named after French mathematician Joseph Fourier and are widely used in signal processing, image processing, and data analysis.

How are Fourier Basis functions different from other basis functions?

Fourier Basis functions have the unique property of being orthogonal to each other, meaning that they are independent and do not overlap. This allows for a more accurate representation of complex signals, as they can be broken down into distinct frequency components.

How do Fourier Basis functions work?

Fourier Basis functions work by breaking down a complex signal into simpler sinusoidal functions with different frequencies and amplitudes. These simpler functions are then combined to form the original signal, allowing for a more efficient representation and analysis of the data.

What are some real-world applications of Fourier Basis functions?

Fourier Basis functions have a wide range of applications in various fields, such as audio and image compression, filtering and noise reduction, pattern recognition, and data analysis. They are also used in engineering and physics to study wave phenomena and in mathematics to solve differential equations.

How can I learn more about Fourier Basis functions?

There are many resources available for learning about Fourier Basis functions, including textbooks, online courses, and tutorials. You can also consult with a mathematician or a signal processing expert for a deeper understanding of their theory and applications.

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