Fast Fourier Transform
The result of Fast fourier transform of a signal is same as that of discrete fourier transform of the same input signal. But, the computational part is reduced in FFT as it uses Cooley and Tuckey's algorithm to compute the result. The algorithm used in FFT computation divides the N point sequence in 2 sequences : even and odd. Thus decomposition reduces calculations.
In this experiment, FFT of 4 point and 8 point sequence was calculated using DITFFT. The comparison of number of real and complex additions and multiplications required for FFT and DFT showed that FFT required less calculations due to parallel processing.
Nicely explained.
ReplyDeleteRadix 2 FFT is faster than Radix 3 FFT
ReplyDeleteFFT is computationally faster than DFT.
ReplyDeleteYes, since some trivial calculations are avoided and parallelism is more.
DeleteFFT is computationally faster than DFT.
ReplyDeleteFFT is used in filtering algorithms
ReplyDeleteAs the length of signal increases the difference between the step of required to get the output goes on increasing
ReplyDeleteFFTs rely on parallel processing algorithms for computational efficiency.
ReplyDeleteFFTs rely on parallel processing algorithms for computational efficiency.
ReplyDeleteFft is faster than DFT
ReplyDelete