comparison DL/Majorization Minimization DL/wrapper_mm_DL.m @ 214:b9b4dc87f1aa luisf_dev

Additional help comments in ~/DL/Majorization Minimization DL/wrapper_mm_DL.m.

 %   Function gets as input Problem and Dictionary Learning (DL) structures 
 %   and outputs the learned Dictionary.
 
 %   In Problem structure field b with the training set needs to be defined.
    
-%   In DL fields with name of the Dictionary update method and parameters
-%   for particular dictionary learning technique need to be present. For 
-%   the orignal version of MM algorithm the update method should be:
+%   In DL structure field with name of the Dictionary update method needs 
+%   to be present. For the orignal version of MM algorithm the update 
+%   method should be:
 %       -   'mm_cn' - Regularized DL with column norm contraint
 %       -   'mm_fn' - Regularized DL with Frobenius norm contraint
 %   Alternatively, for comparison purposes the following Dictioanry update
 %   methods (which do not represent the optimised version of the algorithm)
 %   be used:
 %       -   'mod_cn' - Method of Optimized Direction
 %       -   'map-cn' - Maximum a Posteriory Dictionary update
 %       -   'ksvd-cn'- KSVD update
+%   
+%   DL.param.solver structure is also required. For the original version of
+%   MM algorithm, DL.param.solver.toolbox should be 'MMbox'. The parameters
+%   in DL.param.solver.param should be set accordingly. Type help
+%   wrapper_mm_solver for more details.
 %
 %   -   MM-DL - Yaghoobi, M.; Blumensath, T,; Davies M.; , "Dictionary
 %   Learning for Sparse Approximation with Majorization Method," IEEE
 %   Transactions on Signal Processing, vol.57, no.6, pp.2178-2191, 2009.