# cwtp

0th

Percentile

##### 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

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.

• cwtp
##### 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)

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