Short Time Fourier Transform - invertible?

In summary: And yes, you should be able to recover the original signal using the Inverse STFT. The STFT is invertible, meaning the original signal can be recovered from the transform. This is done by multiplying the Gabor transformed data with the window function, which can also be seen as a form of modulation. Therefore, the original signal can be obtained from the Gabor transformed data.
  • #1
jiapei100
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Short Time Fourier Transform -- invertible?

On Wikipedia,
http://en.wikipedia.org/wiki/Short-time_Fourier_transform"

The STFT is invertible, that is, the original signal can be recovered from the transform by the Inverse STFT.

However, it's also said


It can be seen, comparing to above that windowed "grain" or "wavelet" of x(t) is

http://www.visionopen.com/iGabor.png

the inverse Fourier transform of X(τ,ω) for τ fixed.


That is to say, Gabor is invertible, it's able to obtain the original signal, but modulated.

original signal is obviously x(t),
w(t-τ) is the window function used to extract a local signal within this window,
which can also be looked on as a kind of modulation.

Therefore, in the above function (attached picture),
x(t)w(t-τ) can be computed, from the Gabor transformed data,
But, I'm dropping questions to ask, whether the true original data x(t) can be finally recovered?
as it's declared by Wiki itself
The STFT is invertible, that is, the original signal can be recovered from the transform by the Inverse STFT.


Can anybody help to make me clarified?


Best Regards
JIA Pei
 
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  • #2


I'll answer your question by asking you another question.

Let's say I have a time-varying signal. I multiply it by a gaussian then send it to you. Will you be able to recover the original signal?
 
  • #3


Sorry for my stupidity.

Your word "multiply" hints me. !

This is a "element-wise" multiplication! Right? Yes, it should be.

Thanks for your answering to clarify my doubts.

Best Regards
JIA Pei


IttyBittyBit said:
I'll answer your question by asking you another question.

Let's say I have a time-varying signal. I multiply it by a gaussian then send it to you. Will you be able to recover the original signal?
 
  • #4


Yes, it's element-wise.
 
  • #5


I can confirm that the Short Time Fourier Transform (STFT) is indeed invertible. This means that the original signal can be recovered from the transformed signal using the Inverse STFT. However, it is important to note that the recovered signal may be modulated due to the use of a window function in the STFT.

The window function is used to extract a local signal within a certain time window, and this can be seen as a form of modulation. Therefore, the recovered signal may not be exactly the same as the original signal, but it will still contain the same information. It is important to carefully consider the window function used in the STFT to ensure that the recovered signal is as close to the original signal as possible.

In summary, the STFT is invertible and can be used to recover the original signal, but the use of a window function may result in a modulated signal. Further research and experimentation may be needed to optimize the window function and improve the accuracy of the recovered signal.
 

FAQ: Short Time Fourier Transform - invertible?

What is the Short Time Fourier Transform (STFT)?

The Short Time Fourier Transform (STFT) is a mathematical technique used to analyze and represent a signal or a time series in the frequency domain. It is similar to the standard Fourier Transform, but the STFT allows us to analyze the frequency content of a signal over a short period of time instead of the entire signal.

How is STFT different from the standard Fourier Transform?

The standard Fourier Transform converts a signal from the time domain to the frequency domain, providing information about the entire signal. On the other hand, the STFT divides the signal into smaller, overlapping segments and then applies the Fourier Transform to each segment, giving us a more localized frequency analysis of the signal over time.

Why is the invertibility of STFT important?

The invertibility of STFT is important because it ensures that the original signal can be accurately reconstructed from its STFT representation. This is crucial in applications such as audio and image processing, where the original signal must be reconstructed for further analysis or playback.

How is the STFT made invertible?

The STFT is made invertible by using a window function to isolate each segment of the signal before applying the Fourier Transform. This window function helps to reduce the effects of spectral leakage and allows for accurate reconstruction of the original signal.

What are some common applications of STFT?

The STFT has a wide range of applications in various fields, including audio and speech processing, image processing, radar and sonar signal analysis, and biomedical signal analysis. It is also commonly used in time-frequency analysis and feature extraction for machine learning and data analysis tasks.

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