model=scm_greedy(model, model_data) More...
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Functions | |
function
SCM_data = | scm_coercive_greedy (model, params, operator, innerproduct_matrix) |
model=scm_greedy(model, model_data) More... | |
function C = | scmcoercivegreedy>AddC (mu, model, operator, innerproduct_matrix, SCM_data) |
function
alpha_UB = | scmcoercivegreedy>scm_ub (mu, model, operator, SCM_data) |
function A = | scmcoercivegreedy>remove_dirichlet (A, mode, I) |
model=scm_greedy(model, model_data)
Definition in file scm_coercive_greedy.m.
function SCM_data = scm_coercive_greedy | ( | model, | |
params, | |||
operator, | |||
innerproduct_matrix | |||
) |
model=scm_greedy(model, model_data)
SCM greedy function computes the offline data for the calculation of the coercive constant requires model and model data structure
SCM_data.Ma : number of parameters with an already computed constant near to mu SCM_data.Mp : number of parameters without computed constant near to mu SCM_data.NumberOfParameters : size of the test set used in the SCM Greedy procedure SCM_data.eps : error boundary of the Greedy procedure SCM_data.max_iterations : maximal number of Greedy iterations SCM_data.parallel : = 0 non parallel version = 1 parallel (pool stays active after computaton) = 2 parallel (closing pool afterwards)
David Kreplin 05.01.2015
model | model |
params | params |
operator | operator |
innerproduct_matrix | innerproduct matrix |
SCM_data | SCM data |
para_rand_seed —
para rand seed NumberOfParameters —
NumberOfParameters ParameterSet —
ParameterSet dirichlet_gids —
dirichlet gids eps —
eps parallel —
parallel max_iterations —
max iterationsmu_ranges —
matrix storing the admissable ranges for parameter vector components. Each two dimensional column vector represents a range for a component specified by model.mu_names
.params —
params params.Q —
params.Q lower_bound_coercivity —
lower bound coercivity upper_bound_coercivity —
upper bound coercivity C —
C params.ParameterSet —
params.ParameterSet Definition at line 17 of file scm_coercive_greedy.m.