In this experiment, we performed Fast Fourier transform of 4-point sequence and 8-point sequence.In FFT since all the calculations are done in a parallel manner it is fast.FFT is done in two ways using Decimation in Time and Decimation in Frequency.Here we performed DITFFT so the signal was decimated into parts using Radix-2 Algorithm since the signal is 4 and 8 point sequence using C-programming.Computations in FFT was also performed using a counter and we found that the number of calculation was reduced as compared to DFT so FFT is computationally fast.
Parallel computations are not possible with GPPP
ReplyDeleteFFT's importance derives from the fact that in signal processing and image processing it has made working in frequency domain equally computationally feasible as working in temporal or spatial domain.
ReplyDeleteFFT is fast due to parallel processing.
ReplyDeleteN pt DFT is decomposed into two N/2 pt DFTs, N/2 pt DFT is decomposed into N/4 pt DFTs and so on. Decomposition reduces calculations.
ReplyDeleteFFT requires (NlogN/2) - to the base 2 - number of complex multiplications and NlogN - to the base 2 - number of complex additions
ReplyDeleteComputation in FFT varies logarithmically and all the input in FFT have to be given simultaneously.
ReplyDeleteFourier analysis converts a signal from its original domain to a representation in the frequency domain and vice versa.
ReplyDeleteComputational efficiency is increased as signal is decomposed which makes calculation faster
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