The FFT algorithm divides the N-point input signal into 2 parts-even and odd signal values of the input. Computation is carried out only for N/2 signal values, this increases the speed of computations.
The input & output sequence are in a bit reversed manner.
In this lab session we studied and executed FFT of 4 point and 8 point sequence using DITFFT.
We also calculated no. of computations required to find out FFT of a sequence. Comparing it with that of DFT, we can conclude that FFT is much faster.
The input & output sequence are in a bit reversed manner.
In this lab session we studied and executed FFT of 4 point and 8 point sequence using DITFFT.
We also calculated no. of computations required to find out FFT of a sequence. Comparing it with that of DFT, we can conclude that FFT is much faster.
Can you post why FFT is faster than DFT?
ReplyDeleteFFT is computationally fast, since calculations are performed parallely.
ReplyDeleteFast Fourier Transform are not suitable for real time applications. FFT algorithms are implemented using parallel processing techniques.
ReplyDeleteFFT reduces complex multiplications by decimating the signal to a lower radix.
ReplyDeleteThey cannot be used to find the output of real time system because entire input is not available at an instance of time
ReplyDeleteNumber of computations in FFT is less than that of DFT. This makes FFT computationally faster.
ReplyDeleteFor a better understanding of FFT refer the link below:
ReplyDeleteLink: http://www.earlevel.com/main/2002/08/31/a-gentle-introduction-to-the-fft/
State the Limitations of FFT algorithm?
ReplyDeleteWhy FFT cannot be used for real time applications
ReplyDeletethe signal is divided into 2 parts, so the computation is carried out only for N/2 signal values
ReplyDeleteThis comment has been removed by a blog administrator.
ReplyDeleteFor real time implementation using FFT entire input signal must be available because FFT is parallel computation
ReplyDelete