Monday, 13 March 2017

FFT

In order to overcome the slow computation drawback of DFT , Fast Fourier Transform(FFT) method was invented which performs the same task in less number of steps ,thereby increasing the speed. In this method the input sequence is broken down into two equal parts. This breaking down of the signal was continued till no further decomposition was possible. Radix-2 algorithm is used to perform the experiment. The counter was then added in the code to check the total number of calculations and it was proved that less steps are required to perform the task as compared to DFT.
The difference in the number of steps required goes on increasing as the length of input signal increase.

11 comments:

  1. Replies
    1. Yes, DFT is computationally slower

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    2. As the length of signal increases the difference between the step of required to get the output goes on increasing

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  2. Fft cannot be used for real time processing

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    Replies
    1. Yes this happens because the we cannot predict the length of real time signal.

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    2. Yes this happens because the we cannot predict the length of real time signal.

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  3. FFT can be ussed only for finite length signals which are stored in an array. Only then parallel processing becomes possible

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  4. Number of computations required are less, thus speed increases.

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  5. Gilbert Strang described the FFT as "the most important numerical algorithm of our lifetime"

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    Replies
    1. It cannot be used to process real time signal

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