Function: uwpfbt
UWPFBT Undecimated Wavelet Packet FilterBank Tree
  Usage:  c=uwpfbt(f,wt);
          [c,info]=uwpfbt(...);

  Input parameters:
        f   : Input data.
        wt  : Wavelet Filterbank tree

  Output parameters:
        c   : Coefficients in a L xM matrix.

  c=UWPFBT(f,wt) returns coefficients c obtained by applying the
  undecimated wavelet filterbank tree defined by wt to the input data
  f using the "a-trous" algorithm. Number of columns in c (*M*) is
  defined by the total number of outputs of each node. The outputs c(:,jj)
  are ordered in the breadth-first node order manner.

  [c,info]=UWPFBT(f,wt) additionally returns struct. info containing 
  the transform parameters. It can be conviniently used for the inverse 
  transform IUWPFBT e.g. fhat = iUWPFBT(c,info). It is also required
  by the PLOTWAVELETS function.

  If f is a matrix, the transformation is applied to each of W columns
  and the coefficients in c are stacked along the third dimension.

  Please see help for WFBT description of possible formats of wt.

  Scaling of intermediate outputs:
  --------------------------------

  The following flags control scaling of intermediate outputs and
  therefore the energy relations between coefficient subbands. An 
  intermediate output is an output of a node which is further used as an
  input to a descendant node.

     'intsqrt'
              Each intermediate output is scaled by 1/sqrt(2).
              If the filterbank in each node is orthonormal, the overall
              undecimated transform is a tight frame.
              This is the default.

     'intnoscale'
              No scaling of intermediate results is used. This is
              necessaty for the WPBEST function to correctly work with
              the cost measures.

     'intscale'
              Each intermediate output is scaled by 1/2.

  If 'intnoscale' is used, 'intscale' must be used in IUWPFBT (and vice
  versa) in order to obtain a perfect reconstruction.

  Scaling of filters:
  -------------------

  When compared to WPFBT, the subbands produced by UWPFBT are
  gradually more and more redundant with increasing depth in the tree.
  This results in energy grow of the coefficients. There are 3 flags
  defining filter scaling:

     'sqrt'
              Each filter is scaled by 1/sqrt(a), there a is the hop
              factor associated with it. If the original filterbank is
              orthonormal, the overall undecimated transform is a tight
              frame.
              This is the default.

     'noscale'
              Uses filters without scaling.

     'scale'
              Each filter is scaled by 1/a.

  If 'noscale' is used, 'scale' must be used in IUWPFBT (and vice
  versa) in order to obtain a perfect reconstruction.

  Examples:
  ---------

  A simple example of calling the UWPFBT function using the "full
  decomposition" wavelet tree:

    [f,fs] = greasy;
    J = 6;
    [c,info] = uwpfbt(f,{'db10',J,'full'});
    plotwavelets(c,info,fs,'dynrange',90);

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

See also: iuwpfbt, wfbtinit.

Package: ltfat