Howtosignalprocessing
- What is DFT spectrum?
- Why do we need discrete Fourier transform DFT for signal analysis?
- What is the main difference between DCT and DFT?
- What is the difference between discrete Fourier transform DFT and discrete time Fourier transform DTFT?
What is DFT spectrum?
The discrete Fourier transform (DFT) maps a finite number of discrete time-domain samples to the same number of discrete Fourier-domain samples. Being practical to compute, it is the primary transform applied to real-world sampled data in digital signal processing.
Why do we need discrete Fourier transform DFT for signal analysis?
The Discrete Fourier Transform (DFT) is of paramount importance in all areas of digital signal processing. It is used to derive a frequency-domain (spectral) representation of the signal.
What is the main difference between DCT and DFT?
DCTs are equivalent to DFTs of roughly twice the length, operating on real data with even symmetry (since the Fourier transform of a real and even function is real and even), whereas in some variants the input or output data are shifted by half a sample. There are eight standard DCT variants, of which four are common.
What is the difference between discrete Fourier transform DFT and discrete time Fourier transform DTFT?
original sequence spans all the non-zero values of a function, its DTFT is continuous (and periodic), and the DFT provides discrete samples of one cycle. If the original sequence is one cycle of a periodic Page 2 function, the DFT provides all the non-zero values of one DTFT cycle.
