Discrete Fourier Transform (DFT) is frequency sampled version of Discrete Time Fourier Transform (DTFT).It works on the assumption that input is always periodic, to produce periodic results. In this experiment we had to perform 4 point DFT & 8 point DFT of same input signal.
The magnitude spectrum of both the cases was plotted and compared which helped us draw following conclusion -
As Length of Input SIgnal (N) increases -
1. Frequency Spacing increases.
2. Approximation error decreases.
3. Resolution of spectrum increases.
We also calculated the no. of computations required to gt DFT of a signal and concluded that is DFT computationally slow
The magnitude spectrum of both the cases was plotted and compared which helped us draw following conclusion -
As Length of Input SIgnal (N) increases -
1. Frequency Spacing increases.
2. Approximation error decreases.
3. Resolution of spectrum increases.
We also calculated the no. of computations required to gt DFT of a signal and concluded that is DFT computationally slow
The biggest disadvantage of using DFT over FFT is that it is computationally slow.
ReplyDeleteDFT is a generalized algorithm for frequency domain analysis.
ReplyDeleteIt is frequency sampling of DTFT
ReplyDeleteDFT assumes input signal to be periodic and hence gives discrete spectrum
ReplyDeleteDFT produces periodic results
ReplyDeleteThe twiddle factors all lie on a unit circle; so the more the samples, the more that circle becomes complete, and hence the resolution gets better. The resolution increases because of more twiddle factors taken
ReplyDeleteWhy does DFT gives discrete spectrum?
ReplyDeleteDft is slow as compared to fft
ReplyDeleteDFT is frequency sampled version of DTFT
ReplyDeleteDFT assumes input signal periodic and for periodic signal spectrum is discrete
ReplyDelete