cwtTh {Rwave}

Cauchy's wavelet transform

Description

Compute the continuous wavelet transform with (complex-valued) Cauchy's wavelet.

Usage

cwtTh(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.

nvoice

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

moments

number of vanishing moments.

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 \times nb scales)

3D array (signal size \times noctave \times nvoice)

Value

tmp

continuous (complex) wavelet transform.

References

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

See Also

cwt, cwtp, DOG, gabor.

Examples

    x <- 1:512
    chirp <- sin(2*pi * (x + 0.002 * (x-256)^2 ) / 16)
    retChirp <- cwtTh(chirp, noctave=5, nvoice=12, moments=20)