# cwtp: Continuous Wavelet Transform with Phase Derivative In Rwave: Time-Frequency Analysis of 1-D Signals

 cwtp 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”.

`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)
```

Rwave documentation built on Oct. 22, 2022, 1:05 a.m.