Wavelet packet spectrum
[SPEC,TIMES,FREQ]
= wpspectrum(WPT,Fs)
[...] = wpspectrum(WPT,Fs,'plot')
[...,TNFO] = wpspectrum(...)
[
returns
a matrix of wavelet packet spectrum estimates, SPEC
,TIMES
,FREQ
]
= wpspectrum(WPT
,Fs
)SPEC
,
for the binary wavelet packet tree object, WPT
. Fs
is
the sampling frequency in Hertz. SPEC
is a 2^{J}byN matrix
where J is the level of the wavelet packet transform
and N is the length of the time series. TIMES
is
a 1byN vector of times and FREQ
is
a 1by2^{J} vector of
frequencies.
[...] = wpspectrum(
displays
the wavelet packet spectrum.WPT
,Fs
,'plot')
[...,
returns
the terminal nodes of the wavelet packet tree in frequency order. TNFO
] = wpspectrum(...)



Sampling frequency in Hertz as a scalar of class double. Default: 1 

The character vector 

Wavelet packet spectrum. The frequency spacing between the rows of 

Time vector. 

Frequency vector. 

Terminal nodes. 
wpspectrum
computes the wavelet packet
spectrum as follows:
Extract the wavelet packet coefficients corresponding to the terminal nodes. Take the absolute value of the coefficients.
Order the wavelet packet coefficients by frequency ordering.
Determine the time extent on the original time axis corresponding to each wavelet packet coefficient. Repeat each wavelet packet coefficient to fill in the time gaps between neighboring wavelet packet coefficients and create a vector equal in length to node 0 of the wavelet packet tree object.
Wickerhauser, M.V. Lectures on Wavelet Packet Algorithms, Technical Report, Washington University, Department of Mathematics, 1992.