FFT is a faster and efficient computational method for DFT. Fast Fourier transform reduces the number of computations required considerably when compared with DFT.
The signal is divided into 2 parts; the real and imaginary parts are calculated separately. The result is displayed as Z=X+IY i.e. Z= (real)+i(imaginary).
Thus, for a 4 point signal, two stages will be required which are executed using separate array multiplications.
FFT is used for parallel processing as it improves efficiency.
The signal is divided into 2 parts; the real and imaginary parts are calculated separately. The result is displayed as Z=X+IY i.e. Z= (real)+i(imaginary).
Thus, for a 4 point signal, two stages will be required which are executed using separate array multiplications.
FFT is used for parallel processing as it improves efficiency.
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ReplyDeleteIs the algorithm used by you in this experiment specifically for radix 2 FFT?
ReplyDeleteYes, it is.
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ReplyDeleteFFT uses parallel processing.
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ReplyDeleteFFT is faster than DFT
ReplyDeleteFFT is faster than DFT as it combines common calculations around input samples. Thus, a fixed pattern is established for performing these calculations for input samples.
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