Changeset 895 for applications/bdmtoolbox/tutorial
- Timestamp:
- 04/08/10 16:01:03 (15 years ago)
- Files:
-
- 1 modified
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applications/bdmtoolbox/tutorial/userguide/frg_estim.m
r871 r895 11 11 A1.rv = y; 12 12 A1.rgr = RVtimes([y,u],[-3,-1]) ; 13 A1.log_level = 'logbounds,logevidence';13 A1.log_level = 'logbounds,logevidence'; 14 14 A1.frg = 0.9; 15 15 A1.name = 'A1'; 16 16 17 17 18 %%%%%% Random walk on frg - Dirichlet … … 19 20 phi_pdf.rv = RV({'phi','1_phi'}); % 2D random walk - frg is the first element 20 21 phi_pdf.k = 0.01; % width of the random walk 21 phi_pdf.betac = [0.1 0.1]; % stabilizing elememnt of random walk22 phi_pdf.betac = [0.1 0.1]; % stabilizing elememnt of random walk 22 23 24 %%%%%% Particle 25 p.class = 'MarginalizedParticle'; 26 p.parameter_pdf = phi_pdf; % Random walk is the parameter evolution model 27 p.bm = A1; 28 29 % prior on ARX 23 30 %%%%%% Combining estimators in Marginalized particle filter 24 E.class = 'MPF'; 25 E.BM = A1; % ARX is the analytical part 26 E.parameter_pdf = phi_pdf; % Random walk is the parameter evolution model 31 E.class = 'PF'; 32 E.particle = p; % ARX is the analytical part 27 33 E.res_threshold = 1.0; % resampling parameter 28 34 E.n = 10; % number of particles 29 35 E.prior.class = 'eDirich'; % prior on non-linear part 30 36 E.prior.beta = [2 1]; % 31 E.log_level = 'logbounds,logevidence';37 E.log_level = 'logbounds,logevidence'; 32 38 E.name = 'MPF'; 33 39
