Monday, 13 March 2017

Fast Fourier Transform

Fast Fourier Transform(FFT)

         Discrete Fourier Transform is considered as a computationally slow method. So, the best way to reduce addition and multiplication is using Fast Fourier Transform. Speed matters when implementation of this method comes into picture.
         This session involves taking two cases- 4 point input and 8 point input.In both these cases we execute the code for FFT and study its implementation. This execution enable us to prove its computational advantage.
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6 comments:

  1. Akash Bangera13 March 2017 at 19:55

    FFT improves operational efficiency by using parallel processing.

    ReplyDelete
  2. Tony25 April 2017 at 22:20

    It's also faster in operation as compared to DFT

    ReplyDelete
  3. Ankesh Patil25 April 2017 at 23:12

    FFT is faster

    ReplyDelete
  4. Unknown28 April 2017 at 05:25

    Fft cannot be used for real time processing

    ReplyDelete
  5. Unknown28 April 2017 at 05:36

    Computationally very fast as compared to DFT

    ReplyDelete
  6. Aditi Kajrekar28 April 2017 at 05:56

    Decomposition reduces calculation.

    ReplyDelete

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