DISCRETE FOURIER TRANSFORM

Discrete Fourier Transform, transforms one function into another which is called the frequency domain repreransentation. In this experiment, we found Discrete Fourier Transform of the input signal and then verified it by mathematical formulae. Then we plotted the magnitude spectrum of the output signal and analysed the results. We found that as N(length of the signal) increases,frequency spacing reduces, approximate error reduces and resolution of the spectra increases. DFT  is used to convert signals from Time Domain to Frequency Domain.

Comments

  1. Zaid Ebrahim17 March 2017 at 09:26

    Effect of length on spectra is mentioned which is good

    ReplyDelete
  2. Unknown25 April 2017 at 22:30

    Very informative and well written.

    ReplyDelete
  3. Unknown27 April 2017 at 10:36

    DFT has more computations which makes it slower than FFT

    ReplyDelete
  4. Unknown28 April 2017 at 09:16

    As the length of the signal increases the resolution increases because basically we are taking more samples.

    ReplyDelete
  5. Unknown1 May 2017 at 03:14

    Yes therefore we use FFT for fast computations

    ReplyDelete
  6. Parth1 May 2017 at 07:06

    The magnitude spectrum is periodic due to the characteristic of twiddle factor

    ReplyDelete

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