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