Use of FFT to recover parameters of waves

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Discussion Overview

The discussion centers on the use of Fast Fourier Transform (FFT) to recover parameters from waves, touching on aspects of signal processing and its mathematical foundations. Participants explore introductory concepts, resources, and the complexity involved in applying FFT in practical scenarios.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification
  • Debate/contested
  • Homework-related

Main Points Raised

  • One participant expresses curiosity about using FFT for parameter recovery from waves and requests explanations or references, indicating a background in mathematics but limited knowledge in signal processing.
  • Another participant suggests that understanding Fourier transforms is essential for numerical methods in computer science.
  • A participant warns against underestimating the complexity of Fourier analysis, emphasizing the intense mathematics involved in signal processing.
  • One participant shares a helpful resource for digital signal processing, including FFT, pointing to a specific website.
  • Another participant recommends the USENET group comp.dsp for further inquiries about signal processing, noting its high signal-to-noise ratio.
  • A participant questions the definition of the signal-to-noise ratio as the ratio of the mean to the standard deviation, seeking confirmation on its correctness.

Areas of Agreement / Disagreement

Participants do not reach a consensus on the complexity of FFT and its applications, as some emphasize its challenges while others seek foundational knowledge. The definition of the signal-to-noise ratio also remains unresolved, with a participant questioning its accuracy.

Contextual Notes

Participants express varying levels of familiarity with signal processing concepts, indicating potential gaps in foundational knowledge and assumptions about mathematical prerequisites for understanding FFT.

Who May Find This Useful

This discussion may be useful for individuals interested in signal processing, particularly those at an introductory level seeking resources and clarification on FFT and related concepts.

Bacle
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Hi, everyone:

As I am sure will be clear from my post, I am not--nor have I ever been-- an EE :).
(For the sake of giving some context to help taylor the answer,
I am a mathematician-in-training. I only know the most basic ideas of signal-processing
but I do know --intro-to-mid-level-- statistics: CLT, hypothesis-testing, etc.)

I am just curious on how one can use FFT to recover some parameters from
given waves. Would someone please explaina bit , or suggest a ref? I have read
just a bit on using the mean and likelihood methods to minimize noise.

I was also hoping someone would suggest some good sources at intro
level dealing with signal processing.

Thanks in Advance.
 
Last edited:
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This comes under the topic Numerical Methods in computer science. It might help to know Fourier transforms in advance.
 
Don't assume Fourier is a beast that can be easily tamed! There is some intense mathematics involved in signal processing!
 
UR_Correct said:
Don't assume Fourier is a beast that can be easily tamed! There is some intense mathematics involved in signal processing!

Care to share?
 
I found this site to be enormously helpful in all aspects of digital signal processing, including the FFT: http://www.dspguide.com/"
 
Last edited by a moderator:
i might suggest to go to the USENET group comp.dsp and as them about questions regarding signal processing. it has a pretty high S/N ratio and, if you don't have a newsserver with your ISP, you can always use Google Groups.
 
Thanks to All for your Replies.
rbj:

I recently read in my handbook a definition of the signal-to-noise ratio
in a sample, as the ratio of the mean to the standard deviation. Is this
correct?
 

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