Mercurial > hg > camir-aes2014
comparison toolboxes/FullBNT-1.0.7/bnt/inference/static/@belprop_mrf2_inf_engine/belprop_mrf2_inf_engine.m @ 0:e9a9cd732c1e tip
first hg version after svn
author | wolffd |
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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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-1:000000000000 | 0:e9a9cd732c1e |
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1 function engine = belprop_mrf2_inf_engine(mrf2, varargin) | |
2 % BELPROP_MRF2_INF_ENGINE Belief propagation for MRFs with discrete pairwise potentials | |
3 % engine = belprop_mrf2_inf_engine(mrf2, ...) | |
4 % | |
5 % This is like belprop_inf_engine, except it is designed for mrf2, so is much faster. | |
6 % | |
7 % [ ... ] = belprop_mrf2_inf_engine(..., 'param1',val1, 'param2',val2, ...) | |
8 % allows you to specify optional parameters as name/value pairs. | |
9 % Parameters modifying behavior of enter_evidence are below [default value in brackets] | |
10 % | |
11 % max_iter - max. num. iterations [ 5*nnodes] | |
12 % momentum - weight assigned to old message in convex combination | |
13 % (useful for damping oscillations) [0] | |
14 % tol - tolerance used to assess convergence [1e-3] | |
15 % verbose - 1 means print error at every iteration [0] | |
16 % | |
17 % Parameters can be changed later using set_params | |
18 | |
19 | |
20 % The advantages of pairwise potentials are | |
21 % (1) we can compute messages using vector-matrix multiplication | |
22 % (2) we can easily specify the parameters: one potential per edge | |
23 % In contrast, potentials on larger cliques are more complicated to deal with. | |
24 | |
25 | |
26 nnodes = length(mrf2.adj_mat); | |
27 | |
28 [engine.max_iter, engine.momentum, engine.tol, engine.verbose] = ... | |
29 process_options(varargin, 'max_iter', [], 'momentum', 0, 'tol', 1e-3, ... | |
30 'verbose', 0); | |
31 | |
32 if isempty(engine.max_iter) % no user supplied value, so compute default | |
33 engine.max_iter = 5*nnodes; | |
34 %if acyclic(mrf2.adj_mat, 0) --- can be very slow! | |
35 % engine.max_iter = nnodes; | |
36 %else | |
37 % engine.max_iter = 5*nnodes; | |
38 %end | |
39 end | |
40 | |
41 engine.bel = cell(1, nnodes); % store results of enter_evidence here | |
42 engine.mrf2 = mrf2; | |
43 | |
44 engine = class(engine, 'belprop_mrf2_inf_engine'); | |
45 | |
46 |