comparison examples/MajorizationMinimization tests/SMALL_AMT_DL_test_KSVD_MM.m @ 161:f42aa8bcb82f ivand_dev

debug and clean the SMALLbox Problems code

 
 
 %   Defining Automatic Transcription of Piano tune as Dictionary Learning
 %   Problem
 
-SMALL.Problem = generateAMT_Learning_Problem('',2048,0.75);
+SMALL.Problem = generateAMTProblem('',2048,0.75);
 
 %%
 %   Use KSVD Dictionary Learning Algorithm to Learn 88 notes (defined in
 %   SMALL.Problem.p) using sparsity constrain only
 

 %   (backward compatiblity with SPARCO: solver structure communicate
 %   only with Problem structure, ie no direct communication between DL and
 %   solver structures)
 
 SMALL.Problem.A = SMALL.DL(1).D;
-SMALL.Problem.reconstruct = @(x) SMALL_midiGenerate(x, SMALL.Problem);
+SMALL.Problem.reconstruct = @(x) AMT_reconstruct(x, SMALL.Problem);
 
 %%
 %   Initialising solver structure
 %   Setting solver structure fields (toolbox, name, param, solution, 
 %   reconstructed and time) to zero values

 %   (backward compatiblity with SPARCO: solver structure communicate
 %   only with Problem structure, ie no direct communication between DL and
 %   solver structures)
 
 SMALL.Problem.A = SMALL.DL(2).D;
-SMALL.Problem.reconstruct=@(x) SMALL_midiGenerate(x, SMALL.Problem);
+SMALL.Problem.reconstruct=@(x) AMT_reconstruct(x, SMALL.Problem);
 
 
 %   Call SMALL_soolve to represent the signal in the given dictionary. 
 %   As a final command SMALL_solve will call above defined reconstruction
 %   function to reconstruct the training set (Problem.b) in the learned