The Discrete Fourier Transform (DFT) converts a finite sequence of equally-spaced samples of a function into a finite periodic signal . In this experiment,we observed DFT results for 4 point signal, zero padded 8 point signal and expanded signal. We also plotted magnitude spectrum.
We observed that DFT gives N coefficient values in frequency domain, it gives approximated spectrum. DFT spectrum is defined in the range [0,2π]. We concluded that as length of signal increases the frequency spacing and error decreases on the other hand resolution of spectrum increases. Expansion of signal in time domain gives compress spectrum in frequency domain. Also due to all computations (addition and multiplication)involved ,DFT is computationally slow.
We observed that DFT gives N coefficient values in frequency domain, it gives approximated spectrum. DFT spectrum is defined in the range [0,2π]. We concluded that as length of signal increases the frequency spacing and error decreases on the other hand resolution of spectrum increases. Expansion of signal in time domain gives compress spectrum in frequency domain. Also due to all computations (addition and multiplication)involved ,DFT is computationally slow.
Compression of signal in time domain leads to expansion of signal in frequency domain.
ReplyDeleteBy appending more zeroes, the missing values in less point DFT are present in the DFT with more point.
ReplyDeleteDFT is slower than fft
ReplyDeleteDft is frequency sampling of dtft
ReplyDeleteDFT Produces periodic results.
ReplyDelete