3rd Experiment
The input was for N=4 i.e 4 point FFT. Its Fast Fourier Transform was obtained and the was stored in X[k]. Also IFFT was done too on the output of the first part of this experiment.
Comparision between DFT and FFT was done based on few parameters like Complex Multiplicatio, Complex Addition, Real Multiplication, Real Addtition and from the table it was seen that from the perspective of arithmetic computations the number of arithmetic calculationsin FFT are less than DFT and hence FFT is faster than DFT.
FFt proved faster than DFT
ReplyDeletethat is because of parallel processing
DeleteFFT algorithms are faster ways of doing DFT. It is a family of algorithms and not a single algorithm. How it becomes faster can be explained based on the heart of the algorithm: Divide And Conquer. So rather than working with big size Signals, we divide our signal into smaller ones, and perform DFT of these smaller signals. At the end we add all the smaller DFT to get actual DFT of the big signal. This gives great benefit asymptotically. So for large values of N, we save a lot!
ReplyDeleteEasy to compute as well for large values of N
DeleteNumber of computations required are less, thus speed increases.
ReplyDeleteIt seems FFT is very much preferable over DFT.
ReplyDeleteYes.
ReplyDeleteLess Time as well as Less Computations
FFT cannot be used for real time applications.
ReplyDelete