Solving DFT of f(n*t) vs t Data Array in C

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Discussion Overview

The discussion revolves around how to compute the Discrete Fourier Transform (DFT) of a dataset represented as f(n*t) versus t in the C programming language. Participants are exploring the requirements for performing a DFT, including the need for real and imaginary parts, and how to derive frequency and amplitude from the given data.

Discussion Character

  • Technical explanation
  • Homework-related
  • Debate/contested

Main Points Raised

  • One participant seeks assistance in finding the DFT of their data, noting they only have magnitude values and not the real and imaginary parts.
  • Another participant suggests that if the data is real, the imaginary parts can be set to zero.
  • A participant inquires about how to obtain the value of omega for plotting purposes.
  • Multiple participants provide sample data points for t and X(t) and express a desire to find the DFT, omega/frequency, and X(W) values.
  • One participant questions the level of understanding regarding discrete Fourier transforms and asks what the original poster is trying to determine from the data.
  • A participant expresses a goal to create a frequency versus amplitude graph from the data.
  • Another participant mentions wanting to convert time versus amplitude data into frequency versus amplitude data.
  • One participant challenges the original poster to explain what DFT does, suggesting a lack of understanding of the concept.
  • A later reply advises the original poster to test the DFT with known waveforms, like sine waves, to better understand the frequency spectrum.

Areas of Agreement / Disagreement

There is no consensus on the understanding of DFT among participants, with some expressing confusion about its purpose and others providing suggestions for experimentation. Multiple competing views on how to approach the problem remain unresolved.

Contextual Notes

Participants have not provided specific definitions or assumptions regarding the DFT process, and there are unresolved questions about the necessary data format and the implications of using only magnitude values.

souhal.67
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I have a f(n*t) vs t data areay how to find out its (DFT) Fourier transform in c. I find every time that every program needs its real and imaginarry part. but i have only magnitude. please help me out to find DFT of these data .
 
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If your data is all real then why not put the imaginary values as zero?
 
then how i get the value of omega for ploting
 
after sampling I have value of t & X(t) like
375.020000 -0.754661
375.030000 -0.755227
375.040000 -0.755841
375.050000 -0.756501
375.060000 -0.757207
375.070000 -0.757960
375.080000 -0.758759
375.090000 -0.759604
375.100000 -0.760494
375.110000 -0.761431
375.120000 -0.762414
375.130000 -0.763442
375.140000 -0.764515
375.150000 -0.765633
375.160000 -0.766797
375.170000 -0.768005
375.180000 -0.769258
I would like to find DFT and I need omega/freq and X(W) value
please help me Thank you
 
after sampling I have value of t & X(t) like
375.020000 -0.754661
375.030000 -0.755227
375.040000 -0.755841
375.050000 -0.756501
375.060000 -0.757207
375.070000 -0.757960
375.080000 -0.758759
375.090000 -0.759604
375.100000 -0.760494
375.110000 -0.761431
375.120000 -0.762414
375.130000 -0.763442
375.140000 -0.764515
375.150000 -0.765633
375.160000 -0.766797
375.170000 -0.768005
375.180000 -0.769258
I would like to find DFT and I need omega/freq and X(W) value
please help me Thank you
 
How much do you know about discrete Fourier transforms? What are you trying to find out from the data?
 
Thank you for reply. I want to find out a frequency Vs Amplitude graph
 
I want to find out time vs Amplitude to frequency vs Amplitude of a signal
 
And what does DFT do? (I want you to work a bit for this. ;-) )
 
  • #10
I have a collage project and I have a system out put I must make a program to find out system's frequency response of numerically.
 
  • #11
You didn't say what the DFT does. You have asked a question that suggests you have no idea. I could tell you anything and you would believe me. You need to understand about the process.
If you want an answer then put some data in for a familiar waveform for which you know the frequency spectrum. Try some sine waves with different periods.
 

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