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comparison examples/Automatic Music Transcription/SMALL_AMT_SPAMS_test.m @ 178:4ea4badb2266 danieleb

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added ramirez dl (to be completed) and MOCOD dictionary update
author Daniele Barchiesi <daniele.barchiesi@eecs.qmul.ac.uk>
date Thu, 17 Nov 2011 11:22:17 +0000
parents f42aa8bcb82f
children 9c418bea7f6a
comparison
equal deleted inserted replaced
177:714fa7b8c1ad 178:4ea4badb2266
31 31
32 32
33 % Defining Automatic Transcription of Piano tune as Dictionary Learning 33 % Defining Automatic Transcription of Piano tune as Dictionary Learning
34 % Problem 34 % Problem
35 35
36 SMALL.Problem = generateAMT_Learning_Problem(); 36 SMALL.Problem = generateAMTProblem();
37 TPmax=0; 37 TPmax=0;
38 %% 38 %%
39 for i=1:10 39 for i=1:10
40 %% 40 %%
41 % Solving AMT problem using non-negative sparse coding with 41 % Solving AMT problem using non-negative sparse coding with
75 % (backward compatiblity with SPARCO: solver structure communicate 75 % (backward compatiblity with SPARCO: solver structure communicate
76 % only with Problem structure, ie no direct communication between DL and 76 % only with Problem structure, ie no direct communication between DL and
77 % solver structures) 77 % solver structures)
78 78
79 SMALL.Problem.A = SMALL.DL(i).D; 79 SMALL.Problem.A = SMALL.DL(i).D;
80 SMALL.Problem.reconstruct=@(x) SMALL_midiGenerate(x, SMALL.Problem); 80 SMALL.Problem.reconstruct=@(x) AMT_reconstruct(x, SMALL.Problem);
81 81
82 82
83 %% 83 %%
84 % Initialising solver structure 84 % Initialising solver structure
85 % Setting solver structure fields (toolbox, name, param, solution, 85 % Setting solver structure fields (toolbox, name, param, solution,