Finite Fourier Transform on a 3d wave

In summary, the finite Fourier transform is a mathematical tool used to decompose a function into its frequency components. It works by taking the integral of the function multiplied by a sinusoidal function with a specific frequency. In the case of a 2D wave, the transform can be applied to each dimension separately, resulting in a double integral. However, a 3D Fourier transform can also be used, which would involve a triple integral. The choice of which transform to use depends on the desired outcome.
  • #1
brandy
161
0
Finite Fourier Transform on a 2d wave

How does the finite Fourier transform work exactly?

The transform of f(x) is
[itex]\widetilde{f}(\lambda_{n})[/itex] =[itex]\int[/itex][itex]^{L}_{0}[/itex] f(x) X[itex]_{n}[/itex] dx

If I had a 3d wave equation pde and I applied Finite Fourier transform on the pde for
z(x,y,t)=X(x)Y(y)T(t)

f(x)=z[itex]_{xx}[/itex]
[itex]\tilde{z_{xx}(\lambda_{n})}[/itex] =[itex]\int[/itex][itex]^{L}_{0}[/itex] z[itex]_{xx}[/itex] X[itex]_{n}[/itex](x) dx

f(x)=z[itex]_{yy}[/itex]
[itex]\tilde{z_{yy}(\lambda_{n})}[/itex] =[itex]\int[/itex][itex]^{L}_{0}[/itex] z[itex]_{yy}[/itex] Y[itex]_{n}[/itex](y) dy

etc for T

or

is the transform the same for everything, namely:
f(x)=z[itex]_{xx}[/itex]
[itex]\tilde{z_{xx}(\lambda_{n})}[/itex] =[itex]\int[/itex][itex]^{L}_{0}[/itex] z[itex]_{xx}[/itex] X[itex]_{n}[/itex](x) Y[itex]_{n}[/itex](y) dx

or is it a double integral?
or do you apply finite Fourier twice with respect to y and x.
 
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  • #2
Hi brandy! :smile:

You can take any transform you want, including a 3D Fourier transform, which would be a triple integral.
And also a transform of for instance ##z_{xx}## with respect to y.

In all cases you can apply the Fourier's theorems.
It's just a matter of what you want to achieve.
 
  • #3
Note that you should have a different "frequency" variable for each dimension $x$ and $y$.
 

1. What is the Finite Fourier Transform (FFT) on a 3D wave?

The Finite Fourier Transform on a 3D wave is a mathematical tool used to decompose a 3D signal into its constituent frequencies. It is based on the Fourier series, which states that any periodic signal can be represented as a sum of sinusoidal functions of different frequencies.

2. What is the difference between the FFT and the traditional Fourier Transform?

The FFT is a faster algorithm for computing the Fourier Transform compared to the traditional method, which involves more complex calculations. The FFT is based on the idea of dividing a signal into smaller parts and combining the results, whereas the traditional Fourier Transform involves computing the integral of the signal over its entire domain.

3. What are some applications of the FFT on a 3D wave?

The FFT on a 3D wave has various applications in fields such as signal processing, image processing, and data compression. It is also used in solving differential equations and analyzing complex systems such as fluid dynamics and quantum mechanics.

4. How does the FFT handle non-periodic signals?

The FFT can only be applied to signals that are periodic in nature. However, non-periodic signals can be approximated by repeating them over a specified time interval and then applying the FFT. This is known as zero-padding and is commonly used in signal processing applications.

5. Is the FFT on a 3D wave reversible?

Yes, the FFT on a 3D wave is reversible, meaning that the original signal can be reconstructed from its frequency components. This is known as the inverse FFT and is often used to filter out unwanted frequencies or noise from a signal.

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