{"id":"W2117987480","doi":"10.1109/med.2008.4602143","title":"Dynamical robust nonlinear H&lt;inf&gt;&amp;#x221E;&lt;/inf&gt; filtering for Lipschitz descriptor systems with parametric and nonlinear uncertainties","year":2008,"lang":"en","type":"article","venue":"","topic":"Stability and Control of Uncertain Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Lipschitz continuity; Nonlinear system; Parametric statistics; Robust control; Robustness (evolution); Control theory (sociology); Mathematics; Norm (philosophy); Bounded function; Applied mathematics; Semidefinite programming; Computer science; Mathematical optimization; Pure mathematics; Mathematical analysis; Physics; Law; Control (management); Artificial intelligence; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000586833,0.0006903806,0.0006024152,0.0002131654,0.0002917829,0.001102095,0.0006385901,0.0007011928,0.003451345],"category_scores_gemma":[0.001067374,0.0002266942,0.0005101759,0.0002711401,0.0006143873,0.0007713778,0.0006982883,0.0008484478,0.0006799598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007755262,"about_ca_system_score_gemma":0.0007533708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004073696,"about_ca_topic_score_gemma":0.003318499,"domain_scores_codex":[0.9995717,0.00006239358,0.00002618708,0.0001374083,0.0001646854,0.0000375323],"domain_scores_gemma":[0.9996752,0.0001151963,0.00007554049,0.00004570403,0.00008067999,0.00000771836],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000348016,0.00008513008,0.000754701,0.0004522878,0.00007615561,0.0003262703,0.0002161134,0.6097891,0.04221315,0.09120578,0.004114361,0.250419],"study_design_scores_gemma":[0.00001940083,0.0000786433,0.0001979039,0.00001461559,0.00001153254,0.00003456293,0.00001364423,0.9838885,0.005527863,0.006693823,0.003506305,0.0000131549],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004817838,0.000168668,0.991053,0.00008848261,0.00004137576,0.00002294941,0.00003183221,0.0002158233,0.00355999],"genre_scores_gemma":[0.8143315,0.0008130669,0.164771,0.0002739127,0.0001284834,0.0002441456,0.0004166707,0.000131823,0.01888929],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004073696,"threshold_uncertainty_score":0.0115459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02724843664921184,"score_gpt":0.2067710216903092,"score_spread":0.1795225850410974,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}