Fourier transform is an essential part of signal processing , since it transforms a signal from the time domain into the Frequency domain.
When we have a discrete signal we need to use Discrete Fourier transform is DFT
FFT is an algorithm to compute DFT of any input
FFT is a proven faster method as compared to the DFT algorithm. Some of the similar complexities re-appeared in this code too (example - integration of complex numbers). Unlike the DFT, i could identify patterns in the butterfly diagram taught in the class. Formulating this pattern into a code format and making this code generic(for 4-point and 8-point) and efficient was the real highlight of this code. Though a generic N-point FFT code, still remains an ambitious task.
When we have a discrete signal we need to use Discrete Fourier transform is DFT
FFT is an algorithm to compute DFT of any input
FFT is a proven faster method as compared to the DFT algorithm. Some of the similar complexities re-appeared in this code too (example - integration of complex numbers). Unlike the DFT, i could identify patterns in the butterfly diagram taught in the class. Formulating this pattern into a code format and making this code generic(for 4-point and 8-point) and efficient was the real highlight of this code. Though a generic N-point FFT code, still remains an ambitious task.
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