DOG | R Documentation |

Computes the continuous wavelet transform with for (complex-valued) derivative of Gaussian wavelets.

DOG(input, noctave, nvoice=1, moments, twoD=TRUE, plot=TRUE)

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

`noctave` |
number of powers of 2 for the scale variable. |

`moments` |
number of vanishing moments of the wavelet (order of the derivative). |

`nvoice` |
number of scales in each octave (i.e. between two consecutive powers of 2) |

`twoD` |
logical variable set to T to organize the output as a 2D array (signal_size x nb_scales), otherwise, the output is a 3D array (signal_size x noctave x nvoice) |

`plot` |
if set to T, display the modulus of the continuous wavelet transform on the graphic device |

The output contains the (complex) values of the wavelet transform of the input signal. The format of the output can be

2D array (signal_size x nb_scales)

3D array (signal_size x noctave x nvoice)

continuous (complex) wavelet transform

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

`cwt`

, `cwtp`

, `cwtsquiz`

,
`cgt`

.

x <- 1:512 chirp <- sin(2*pi * (x + 0.002 * (x-256)^2 ) / 16) DOG(chirp, noctave=5, nvoice=12, 3, twoD=TRUE, plot=TRUE)

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