Definition clarification for Fourier transform

In summary, there are two versions of the forward and inverse Fourier transforms, one with a positive and one with a negative exponent in the integrand. Only the second version is correct, but it is a matter of convention. The exponent must change for the inverse transform relative to the forward transform. It is also possible to perform a multiple dimensional Fourier transform using volume integrals, but the formula varies depending on convention and typically includes the square root of 2π.
  • #1
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I have been studying Fourier transforms lately. Specifically, I have been studying the form of the formula that uses the square root of 2π in the definition. Now here is the problem:

In some sources, I see the forward and inverse transforms defined as such:
F(k) = [1/(√2π)] ∫-∞ f(x)eikx dx
f(x) = [1/(√2π)] ∫-∞ f(k)eikx dkIn other cases, I've seen:
F(k) = [1/(√2π)] ∫-∞ f(x)e-ikx dx
f(x) = [1/(√2π)] ∫-∞ f(k)eikx dk

Notice that in the first version of the forward transform (the one that solves for F(k)), the exponential in the integrand has a positive sign in the exponent ikx, while in the 2nd version it has a negative ikx.

Which version is correct? Are they both correct and it is a matter of convention? Are neither correct?

Also, is there some way to do a multiple dimensional Fourier transform using volume integrals? If so, what is the formula for that (preferably including (√2π))?
 
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  • #2
Only the 2nd pair is correct. There are a couple conventional issues, but no matter what the sign on the exponent has to change for the inverse transform relative to the forward transform.
 

Related to Definition clarification for Fourier transform

1. What is the definition of Fourier transform?

The Fourier transform is a mathematical operation that decomposes a signal into its constituent frequencies. It is commonly used in signal processing, image processing, and other fields to analyze and manipulate signals in the frequency domain.

2. How is the Fourier transform calculated?

The Fourier transform is calculated by taking the complex integral of a signal over a given range of frequencies. This integral is typically solved using numerical methods, although there are also analytical solutions for some signals.

3. What is the difference between the Fourier transform and the inverse Fourier transform?

The Fourier transform converts a signal from the time domain to the frequency domain, while the inverse Fourier transform converts a signal from the frequency domain back to the time domain. They are essentially inverse operations of each other.

4. Can the Fourier transform be applied to any type of signal?

Yes, the Fourier transform can be applied to any signal that is continuous and has a finite energy, such as audio signals, images, and electronic signals. However, it is most commonly used for signals that are periodic or have a repeating pattern.

5. Are there any limitations or drawbacks to using the Fourier transform?

One limitation of the Fourier transform is that it assumes the signal is periodic, which may not always be the case in real-world signals. Additionally, the Fourier transform can be computationally expensive for signals with a large number of data points, and it may not be suitable for analyzing signals with sudden changes or discontinuities.

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