cgt | R Documentation |

Computes the continuous Gabor transform with Gaussian window.

cgt(input, nvoice, freqstep=(1/nvoice), scale=1, plot=TRUE)

`input` |
input signal (possibly complex-valued). |

`nvoice` |
number of frequencies for which gabor transform is to be computed. |

`freqstep` |
Sampling rate for the frequency axis. |

`scale` |
Size parameter for the window. |

`plot` |
logical variable set to TRUE to display the modulus of the continuous gabor transform on the graphic device. |

The output contains the (complex) values of the gabor transform of the input signal. The format of the output is a 2D array (signal_size x nb_scales).

continuous (complex) gabor transform (2D array).

freqstep must be less than 1/nvoice to avoid aliasing. freqstep=1/nvoice corresponds to the Nyquist limit.

See discussion in text of “Practical Time-Frequency Analysis”.

`cwt`

, `cwtp`

, `DOG`

for continuous wavelet transforms.
`cwtsquiz`

for synchrosqueezed wavelet transform.

data(HOWAREYOU) plot.ts(HOWAREYOU) cgtHOWAREYOU <- cgt(HOWAREYOU,70,0.01,100)

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