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file | fast_eigs.m [code] |
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file | SCM.m [code] |
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file | scm_coercive_demo.m [code] |
| scm_coercive_demo()
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file | scm_coercive_greedy.m [code] |
| model=scm_greedy(model, model_data)
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file | scm_coercive_lb.m [code] |
| alpha_LB = scm_lb(mu,model,model_data) computation of the lowerbound of the coercive constant equal to the coercive constant computet via SCM
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file | scm_demo.m [code] |
| scm_demo.m a simple demo script which produces scm_offline_data for the inf-sup constant of the scm_minimal_model. Then for a fine set of parameters in [0,1] the exact constant beta(mu), the lower bound beta_{LB}(mu) and the exact cercivity constant alpha(mu) are computet and the results are plottet. This shows that the scm_minimal_model is coercive up to mu = 0.5 and from there on it is only inf-sup stable. For mu = 0.5 it is neither cercive nor inf-sup stable. The main point is to show, that the SCM is working fine for little lin_stat inf-sup stable problems.
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file | scm_get_neighbours.m [code] |
| [P_M, ind] = scm_get_neighbours(M, mu, C)
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file | scm_infsup_demo.m [code] |
| scm_infsup_demo()
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file | scm_infsup_greedy.m [code] |
| model=scm_greedy(model, model_data)
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file | scm_infsup_lb.m [code] |
| alpha_LB = scm_infsup_lb(mu,model,model_data) computation of the lowerbound of the coercive constant equal to the coercive constant computet via SCM
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file | scm_lower_bound.m [code] |
| [constant_LB, constant_UB] = scm_lower_bound(model, reduced_data)
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file | scm_minimal_model.m [code] |
| model = scm_minimal_model(size)
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file | scm_offline.m [code] |
| scm_offline_data = scm_offline(model, detailed_data, M_train, D_train)
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file | scm_online.m [code] |
| scm_results = scm_online(mu, Theta_mu, scm_offline_data, M_alpha, M_plus, desired_constant)
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file | SCMonline.m [code] |
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