Mercurial > hg > camir-aes2014
diff toolboxes/FullBNT-1.0.7/bnt/CPDs/@hhmmF_CPD/hhmmF_CPD.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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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/toolboxes/FullBNT-1.0.7/bnt/CPDs/@hhmmF_CPD/hhmmF_CPD.m Tue Feb 10 15:05:51 2015 +0000 @@ -0,0 +1,73 @@ +function CPD = hhmmF_CPD(bnet, self, Qself, Fbelow, varargin) +% HHMMF_CPD Make the CPD for an F node in a hierarchical HMM +% CPD = hhmmF_CPD(bnet, self, Qself, Fbelow, ...) +% +% Qps +% \ +% \ +% Fself +% / | +% / | +% Qself Fbelow +% +% We assume nodes are ordered (numbered) as follows: Qps, Q, Fbelow, F +% All nodes numbers should be from slice 1. +% +% If Fbelow if missing, this becomes a regular tabular_CPD. +% Qps may be omitted. +% +% optional args [defaults] +% +% Qps - node numbers. +% termprob - termprob(k,i,2) = prob finishing given Q(d)=i and Q(1:d-1)=k [ finish in last state wp 0.9] +% +% hhmmF_CPD is a subclass of tabular_CPD so we inherit inference methods like CPD_to_pot, etc. +% +% We create an isolated tabular_CPD with no F parent to learn termprob +% so we can avail of e.g., entropic or Dirichlet priors. +% +% For details, see "Linear-time inference in hierarchical HMMs", Murphy and Paskin, NIPS'01. + + + +Qps = []; +% get parents +for i=1:2:length(varargin) + switch varargin{i}, + case 'Qps', Qps = varargin{i+1}; + end +end + +ns = bnet.node_sizes(:); +Qsz = ns(Qself); +Qpsz = prod(ns(Qps)); +CPD.Qsz = Qsz; +CPD.Qpsz = Qpsz; + +ps = parents(bnet.dag, self); +CPD.Fbelow_ndx = find_equiv_posns(Fbelow, ps); +CPD.Qps_ndx = find_equiv_posns(Qps, ps); +CPD.Qself_ndx = find_equiv_posns(Qself, ps); + +% set default arguments +p = 0.9; +%termprob(k,i,t) Might terminate if i=Qsz; will not terminate if i<Qsz +termprob = zeros(Qpsz, Qsz, 2); +termprob(:, Qsz, 2) = p; +termprob(:, Qsz, 1) = 1-p; +termprob(:, 1:(Qsz-1), 1) = 1; + +for i=1:2:length(varargin) + switch varargin{i}, + case 'termprob', termprob = varargin{i+1}; + end +end + +CPD.sub_CPD_term = mk_isolated_tabular_CPD([Qpsz Qsz 2], {'CPT', termprob}); +S = struct(CPD.sub_CPD_term); +CPD.termprob = S.CPT; + +CPD = class(CPD, 'hhmmF_CPD', tabular_CPD(bnet, self)); + +CPD = update_CPT(CPD); +