Sum-product algorithm toolbox version 1.5.2

One minor change to the previous version (1.5.0) is we make ITSBN+EM a function which can be called by any main code. This makes the code look more concise and systematical.

fn_EM_ITSBN.m

[] = fn_EM_ITSBN(L, connectivity, value, H, N,...

discrete_node_list, continuous_node_list,...

hidden_node_list, observed_node_list,...

tie_level_table, tie_parameter_table)

Input

Here are the necessary input for EM for ITSBN

• L: The number of DISCRETE-node levels of ITSBN, including only the discrete nodes because in ITSBN every discrete node has its own continuous node already, hence need not to count them.
• N: The total number of nodes (both discrete and continuous) in the network
• H: the L x 2 cell array. H{l,1} contains the level number and H{l,2} contains the list of DISCRETE node indices in the level l
• connectivity: The structure of the ITSBN is defined via this (N-1) x 2 matrix. The format of the matrix is discussed in the code documentation of the first version already.
• value: the N x 1 cell array containing the value at each observed node
• discrete_node_list
• continuous_node_list
• hidden_node_list
• observed_node_list
• tie_level_table
• tie_parameter_table

output

The function output a .mat file result_EM_ITSBN.mat which contains the following variables:

• x_best: The best structure of variable nodes x when the EM is finished
• f_best: The best structure of factor nodes f when the EM is finished
• best_ll: the best log-likelihood value through the EM process
• iteration_EM_converge: the total number of iterations before converged
• marg_post_mat_best: the N x 1 cell array storing the best posterior marginal