Number of computations required in DFT are large which is not suitable for real time systems. To overcome this problem we use Fast Fourier Transform(FFT). Radix-2 FFT was calculated according to the butterfly diagram for N=4 and N=8. The computations required for FFT i.e. the number of real and complex multiplications and additions was found out through the code and verified with the formula. Thus FFT proved to be computationally efficient.
Can you explain how many computations are required in the case of DFT and FFT?
ReplyDeleteComputing the DFT of N points using the definition, takes (N*N) arithmetical operations, while an FFT can compute the same DFT in only (N*log N) operations.
ReplyDeleteFFT is faster than DFT
ReplyDeleteRadix 2 FFT requires minimum no. of computations.
ReplyDeleteHow to mathematically calculate the no of computations?
ReplyDeleteFFT use parallel processing technique
ReplyDeleteFft is faster than dft
ReplyDelete