fft
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Compute the discrete fourier transform of a real signal using the fft or the dft algorithm.
- Usage 1
fft(n)
- n
- desired signal window length (scalar)
- Result 1
- The next (nearest) possible signal window length.
- Usage 2
fft(x)
- x
- signal vector or matrix; if x is a matrix a spectrum of each column is computed
- Result 2
- A matrix y with ncol(x) columns and L+2 rows, where each column y[*,j] contains the complex spectrum of the column (channel) x[*,i]. The transformation length L is set to npow2(nrow(x)).
- Usage 3
fft(x, n {, ytype, poffset, prange, aref})
- x
- signal vector or matrix; if x is a matrix a spectrum of each column is computed
- n
- desired length of analysis window;
- If
n < nrow(x)
, the analysis window length L is set to nrow(x), otherwise L is set to n. - If the analysis window length L is a power of 2 (L=2^M), the fft algorithm is used, otherwise the dft is used.
- If L is greater than nrow(x), zero padding is applied to the signal.
- If
- ytype
- select the type and format of the computed spectrum (see Result 3)
- poffset
- offset in samples to the signal begin or the selected zero phase position (default=0)
poffset='0 -> phase[i] = atan2(im[i], re[i])
otherwise -> phase[i] = (atan2(im[i], re[i]) - 2*pi*i/L * poffset) % (2 * pi)