Mercurial > hg > camir-aes2014
comparison toolboxes/FullBNT-1.0.7/bnt/examples/dynamic/chmm1.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 % Compare the speeds of various inference engines on a coupled HMM | |
2 | |
3 N = 3; | |
4 Q = 2; | |
5 rand('state', 0); | |
6 randn('state', 0); | |
7 discrete = 0; | |
8 if discrete | |
9 Y = 2; % size of output alphabet | |
10 else | |
11 Y = 3; % size of observed vectors | |
12 end | |
13 coupled = 1; | |
14 bnet = mk_chmm(N, Q, Y, discrete, coupled); | |
15 %bnet = mk_fhmm(N, Q, Y, discrete); % factorial HMM | |
16 ss = length(bnet.node_sizes_slice); | |
17 | |
18 T = 3; | |
19 | |
20 USEC = exist('@jtree_C_inf_engine/collect_evidence','file'); | |
21 | |
22 engine = {}; | |
23 engine{end+1} = jtree_dbn_inf_engine(bnet); | |
24 %engine{end+1} = jtree_ndx_dbn_inf_engine(bnet, 'ndx_type', 'SD'); | |
25 %engine{end+1} = jtree_ndx_dbn_inf_engine(bnet, 'ndx_type', 'D'); | |
26 %engine{end+1} = jtree_ndx_dbn_inf_engine(bnet, 'ndx_type', 'B'); | |
27 if USEC, engine{end+1} = jtree_C_dbn_inf_engine(bnet); end | |
28 engine{end+1} = hmm_inf_engine(bnet); | |
29 engine{end+1} = jtree_unrolled_dbn_inf_engine(bnet, T); | |
30 | |
31 % times in matlab N=4 Q=4 T=5 (* = winner) | |
32 % jtree SD B hmm dhmm unrolled | |
33 % 0.6266 1.1563 8.3815 0.3069 0.1948* 0.8654 inf | |
34 % 0.9057* 2.1522 12.6314 2.6847 2.3107 3.1905 learn | |
35 | |
36 %engine{end+1} = bk_inf_engine(bnet, 'ff', onodes); | |
37 %engine{end+1} = pearl_unrolled_dbn_inf_engine(bnet, T); | |
38 | |
39 inf_time = cmp_inference_dbn(bnet, engine, T) | |
40 learning_time = cmp_learning_dbn(bnet, engine, T) | |
41 |