In today's world, real time processing of signals is required, be it in stock markets or industrial applications, where even a difference of a seconds can lead to losses in millions. Hence, using conventional DFT algorithm is not feasible and Fast Fourier Transform was developed by two friends Cooley and Tukey in 1965.
We studied implementing FFT using Radix-2 Decimation In Time Fast Fourier Transform(DITFFT) algorithm. The signal is decimated in time domain which helps to reduce the number of complex calculations. This, in turn increases the speed of processing. The order of the inputs and outputs are in a bit reversed manner.
For example, when N=4; while DFT takes 240 real additions and 256 real multiplications, the numbers in FFT are reduced to 16 and 48 respectively!!
Thus, FFT is faster, efficient and more easily realizable at higher values of N.
Thanks @Amol
ReplyDeleteDFT is slower
ReplyDeleteYes, DFT is slower
DeleteFFT is faster method than DFT.
ReplyDeleteYes, FFT is comparatively faster
Deletefft requires less computations
ReplyDeleteYes, FFT requires less number of computations and is faster
DeleteIn FFT, we use parallel processing method
ReplyDeleteYes, FFT is faster method than DFT
DeleteIn FFT, we use parallel processing
ReplyDeleteFFT is a big milestone in the history of signal processing and it lead to more faster adaptation of digital signal processing.
ReplyDeleteNumber of real and complex additions and multiplications is less for the same order in FFT
ReplyDeleteRadix 2 FFT is the most common method
ReplyDeleteFFT is used in practical systems for frequency domain analysis.
ReplyDelete