# cwtp

##### Continuous Wavelet Transform with Phase Derivative

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

- Keywords
- ts

##### 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 \(\times\) nb scales), otherwise, the output is a 3D array (signal size \(\times\) noctave \(\times\) 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

array of complex numbers for the values of the continuous wavelet transform.

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

```
# NOT RUN {
## 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)
# }
```

*Documentation reproduced from package Rwave, version 2.4-8, License: GPL (>= 2)*