WAVFUN Wavelet Function
Usage: [w,s,xvals] = wavfun(g)
[w,s,xvals] = wavfun(g,N)
Input parameters:
w : Wavelet filterbank
N : Number of iterations
Output parameters:
wfunc : Approximation of wavelet function(s)
sfunc : Approximation of the scaling function
xvals : Correct x-axis values
Iteratively generate (*N iterations) a discrete approximation of wavelet
and scaling functions using filters obtained from w. The possible formats of w*
are the same as for the FWT function. The algorithm is equal to the
DWT reconstruction of a single coefficient at level N+1 set to 1. xvals*
contains correct x-axis values. All but last columns belong to the
wfunc, last one to the sfunc.
The following flags are supported (first is default):
'fft', 'conv'
How to do the computations. Whatever is faster depends on
the speed of the conv2 function.
*WARNING**: The output array lengths L depend on N exponentially like:
L=(m-1)*(a^N-1)/(a-1) + 1
where a is subsamling factor after the lowpass filter in the wavelet
filterbank and m is length of the filters. Expect issues for
high N e.g. 'db10' (m=20) and N=20 yields a ~150MB array.
Examples:
---------
Approximation of a Daubechies wavelet and scaling functions from the
12 tap filters:
[wfn,sfn,xvals] = wavfun('db6');
plot(xvals,[wfn,sfn]);
legend('wavelet function','scaling function');
Package: ltfat