FFT is a faster computational method compared to DFT as the signal is divided into even and odd parts and computations for both are done alongside. We see that the first value is always the sum of input signal values.
We have taken two sequences 4pt and 8 pt. and found their Fast Fourier Transforms to study these radix 2 FFT algorithms. The computation is carried out only for N/2 values and makes it the fastest algorithm computationally.
How do you know it's computationally faster?
ReplyDeleteAs we split the odd and even values before we use the FFT algorithm on them and the computation occurs simultaneously for odd and even parts, FFT holds an upper hand in computational speed.
DeleteAre there different methods to find FFT?
ReplyDeleteYes there are different algorithms to find FFT. We mainly use the Cooley-Tukey algorithm. There's exist other algorithms such as Prime factor FFT, Brunns FFT, Hexagonal FFT etc to which we haven't quite been introduced yet
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ReplyDeleteFFt is better than Dft due to decomposition which reduces the no. of computations.
ReplyDeleteFFT uses parallel processing
ReplyDeleteYes hence it is faster
DeleteHow do you get paralell input in real time for FFT applications?
ReplyDeleteAny signal can be split into its odd and even parts and computed paralelly
DeleteWe should opt for DSP processor as by using intel processor for fft computation parallel processing is difficult to achieve by c compiler.
ReplyDeleteTrue.. dsp processor will make the job easier
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