DOG {Rwave}

Continuous Wavelet Transform with derivative of Gaussian

Description

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

Usage

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

Arguments

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

Details

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)

Value

continuous (complex) wavelet transform

References

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

See Also

cwt, cwtp, cwtsquiz, cgt.

Examples

 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)