Is the Discrete Fourier Transform a Unitary Transformation?

In summary: Adding the ##\frac{1}{\sqrt{N}}## factor will make the matrix unitary.In summary, the conversation discusses the process of proving the discrete form of the Fourier transform is a unitary transformation. The equation for the discrete Fourier transform is used and put into a matrix form, but it is found that without the factor of ##1/\sqrt{N}##, the matrix is not unitary. It is then clarified that a unitary matrix must have its adjoint as its inverse, not its complex conjugate. The conversation ends with the understanding that adding the ##\frac{1}{\sqrt{N}}## factor will make the matrix unitary.
  • #1
Emperor42
15
0
I'm trying to prove that the discrete form of the Fourier transform is a unitary transformation

So I used the equation for the discrete Fourier transform:
##y_k=\frac{1}{\sqrt{N}}\sum^{N-1}_{j=0}{x_je^{i2\pi\frac{jk}{N}}}##

and I put the Fourier transform into a N-1 by N-1 matrix form:
##U=\begin{pmatrix}
e^0 & e^0 & e^0 & ...\\
e^0 & e^{\frac{i2\pi}{N}} & e^{\frac{i4\pi}{N}} & ...\\
e^0 & e^{\frac{i4\pi}{N}} & e^{\frac{i8\pi}{N}} & ...\\
... & ... & ... & ...\\
\end{pmatrix}##

and then found the complex conjugate:
##U^*=\begin{pmatrix}
e^0 & e^0 & e^0 & ...\\
e^0 & e^{-\frac{i2\pi}{N}} & e^{-\frac{i4\pi}{N}} & ...\\
e^0 & e^{-\frac{i4\pi}{N}} & e^{-\frac{i8\pi}{N}} & ...\\
... & ... & ... & ...\\
\end{pmatrix}##

But if I multiply these matrices together I get nothing which even approaches the identity matrix. Anyone have any ideas? Is there something wrong with the matrix?
 
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  • #2
You omitted the factor of ##1/\sqrt{N}##. Without it, the matrix won't be unitary. Also, the inverse of a unitary matrix is its adjoint, not the complex conjugate.
 
  • #3
I understand that I haven't put in the ##\frac{1}{\sqrt{N}}##. But why do I need the inverse? I'm trying to calculate whether the matrix is unitary so I need to find the inner product of the matrix and its complex conjugate, wouldn't I?
 
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  • #4
Ok I think I can get the diagonal elements to go to if I add the ##\frac{1}{\sqrt{N}}## factor but I still don't understand how the off diagonal elements go to zero.
 
  • #5
Emperor42 said:
I understand that I haven't put in the ##\frac{1}{\sqrt{N}}##. But why do I need the inverse? I'm trying to calculate whether the matrix is unitary so I need to find the inner product of the matrix and its complex conjugate, wouldn't I?
No. Unitary means that the inverse of the matrix is its adjoint. In other words, if you multiply a unitary matrix by its adjoint (not conjugate), you get the identity matrix, which is what you're trying to show.
 

FAQ: Is the Discrete Fourier Transform a Unitary Transformation?

What is a unitary discrete Fourier transform?

A unitary discrete Fourier transform (DFT) is a mathematical operation that converts a discrete signal from the time domain to the frequency domain. It decomposes a signal into its individual frequency components, allowing for analysis and processing in the frequency domain.

How is a unitary DFT different from a regular DFT?

A unitary DFT is a specific type of DFT that preserves the energy and magnitude of the original signal. This means that the inverse unitary DFT will produce the exact same signal as the original input, whereas a regular DFT may introduce errors due to the loss of energy during the transformation.

What are the applications of unitary DFT?

Unitary DFT has various applications in signal processing, data compression, image processing, and audio analysis. It is also used in digital communication systems, spectral analysis, and filtering.

How is a unitary DFT calculated?

A unitary DFT is calculated using a mathematical formula called the Fast Fourier Transform (FFT). The FFT algorithm efficiently computes the DFT of a signal by breaking it down into smaller sub-problems, making the computation faster and more efficient.

What are the advantages of using a unitary DFT?

The main advantage of using a unitary DFT is that it preserves the energy and magnitude of the input signal, ensuring accurate analysis and processing in the frequency domain. Additionally, the FFT algorithm used to calculate the unitary DFT is faster and more efficient than other methods, making it a popular choice in various applications.

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