R: Continuous Wavelet Transform with Phase Derivative

cwtp {Rwave} | R Documentation

## Continuous Wavelet Transform with Phase Derivative

### Description

Computes the continuous wavelet transform with (complex-valued) Morlet wavelet and its phase derivative.

### Usage

    cwtp(input, noctave, nvoice=1, w0=2 * pi, 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).
`w0` | central frequency of the wavelet.
`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 `TRUE`, display the modulus of the continuous wavelet transform on the graphic device.

### Value

list containing the continuous (complex) wavelet transform and the phase derivative

`wt` | array of complex numbers for the values of the continuous wavelet transform.
`f` | array of the same dimensions containing the values of the derivative of the phase of the continuous wavelet transform.

### References

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

### See Also

`cgt`, `cwt`, `cwtTh`, `DOG` for wavelet transform, and `gabor` for continuous Gabor transform.

### Examples

        ## discards imaginary part with error,
        ## c code does not account for Im(input)
        x <- 1:512
        chirp <- sin(2*pi * (x + 0.002 * (x-256)^2 ) / 16)
        chirp <- chirp + 1i * sin(2*pi * (x + 0.004 * (x-256)^2 ) / 16)
        retChirp <- cwtp(chirp, noctave=5, nvoice=12)

[Package Rwave version 2.4-8 Index]