R: Cauchy's wavelet transform

cwtTh {Rwave} | R Documentation

## 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 x nb scales)

3D array (signal size x noctave x 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)

[Package Rwave version 2.5-0 Index]