Function: wavfun
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');

Url: http://ltfat.github.io/doc/wavelets/wavfun.html

Package: ltfat