diff options
Diffstat (limited to 'sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private')
5 files changed, 69 insertions, 0 deletions
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/CVS/Entries b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/CVS/Entries new file mode 100644 index 00000000..9a351a87 --- /dev/null +++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/CVS/Entries @@ -0,0 +1,3 @@ +/dbn_to_lds.m/1.1.1.1/Wed May 29 15:59:56 2002// +/extract_params_from_gbn.m/1.1.1.1/Wed May 29 15:59:56 2002// +D diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/CVS/Repository b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/CVS/Repository new file mode 100644 index 00000000..3f67aee0 --- /dev/null +++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/CVS/Repository @@ -0,0 +1 @@ +FullBNT/BNT/inference/dynamic/@kalman_inf_engine/private diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/CVS/Root b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/CVS/Root new file mode 100644 index 00000000..f3bd14a6 --- /dev/null +++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/CVS/Root @@ -0,0 +1 @@ +:ext:nsaunier@bnt.cvs.sourceforge.net:/cvsroot/bnt diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/dbn_to_lds.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/dbn_to_lds.m new file mode 100644 index 00000000..6249ac0d --- /dev/null +++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/dbn_to_lds.m @@ -0,0 +1,26 @@ +function [trans_mat, trans_cov, obs_mat, obs_cov, init_state, init_cov] = dbn_to_lds(bnet) +% DBN_TO_LDS Compute the Linear Dynamical System parameters from the Gaussian DBN. +% [trans_mat, trans_cov, obs_mat, obs_cov, init_state, init_cov] = dbn_to_lds(bnet) + +onodes = bnet.observed; +ss = length(bnet.intra); +num_nodes = ss*2; +assert(isequal(bnet.cnodes_slice, 1:ss)); +[W,D,mu] = extract_params_from_gbn(bnet); + +hnodes = mysetdiff(1:ss, onodes); +bs = bnet.node_sizes(:); % block sizes + +obs_mat = W(block(hnodes,bs), block(onodes,bs))'; +u = block(onodes,bs); +obs_cov = D(u,u); + +trans_mat = W(block(hnodes,bs), block(hnodes + ss, bs))'; +u = block(hnodes + ss, bs); +trans_cov = D(u,u); + +u = block(hnodes,bs); +init_cov = D(u,u); +init_state = mu(u); + + diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/extract_params_from_gbn.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/extract_params_from_gbn.m new file mode 100644 index 00000000..86345830 --- /dev/null +++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/extract_params_from_gbn.m @@ -0,0 +1,38 @@ +function [B,D,mu] = extract_params_from_gbn(bnet) +% Extract all the local parameters of each Gaussian node, and collect them into global matrices. +% [B,D,mu] = extract_params_from_gbn(bnet) +% +% B(i,j) is a block matrix that contains the transposed weight matrix from node i to node j. +% D(i,i) is a block matrix that contains the noise covariance matrix for node i. +% mu(i) is a block vector that contains the shifted noise mean for node i. + +% In Shachter's model, the mean of each node in the global gaussian is +% the same as the node's local unconditional mean. +% In Alag's model (which we use), the global mean gets shifted. + + +num_nodes = length(bnet.dag); +bs = bnet.node_sizes(:); % bs = block sizes +N = sum(bs); % num scalar nodes + +B = zeros(N,N); +D = zeros(N,N); +mu = zeros(N,1); + +for i=1:num_nodes % in topological order + ps = parents(bnet.dag, i); + e = bnet.equiv_class(i); + %[m, Sigma, weights] = extract_params_from_CPD(bnet.CPD{e}); + s = struct(bnet.CPD{e}); % violate privacy of object + m = s.mean; Sigma = s.cov; weights = s.weights; + if length(ps) == 0 + mu(block(i,bs)) = m; + else + mu(block(i,bs)) = m + weights * mu(block(ps,bs)); + end + B(block(ps,bs), block(i,bs)) = weights'; + D(block(i,bs), block(i,bs)) = Sigma; +end + + + |