{"id":"W2744953493","doi":"10.1016/j.ifacol.2017.08.061","title":"Three examples of the stability properties of the invariant extended Kalman filter","year":2017,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Safran Electronics (Canada)","funders":"","keywords":"Extended Kalman filter; Invariant extended Kalman filter; Control theory (sociology); Kalman filter; Multiplicative function; Alpha beta filter; Convergence (economics); Computer science; Unscented transform; Mathematics; Artificial intelligence; Moving horizon estimation; Mathematical analysis","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004864428,0.0001662967,0.0002530966,0.00001929018,0.0005309903,0.0001072497,0.003412911,0.00008209753,0.00005494875],"category_scores_gemma":[0.0004131353,0.00007972394,0.0001688546,0.0001162914,0.0005546794,0.0002883533,0.001352457,0.0002363492,0.000003770353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001564797,"about_ca_system_score_gemma":0.00009235893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006060825,"about_ca_topic_score_gemma":0.0009941398,"domain_scores_codex":[0.9984489,0.0001176957,0.0003732608,0.0003634086,0.0004471491,0.0002495934],"domain_scores_gemma":[0.9960432,0.00009930933,0.000419129,0.003245463,0.0001453131,0.00004757468],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000335848,0.002151842,0.1923333,0.0007356243,0.0003828732,0.00001827567,0.01561137,0.0009317159,0.5769156,0.06654619,0.0009387405,0.1430986],"study_design_scores_gemma":[0.001004941,0.0001215794,0.7999896,0.0005599348,0.00005201362,0.00002260378,0.0002638088,0.04147895,0.1506136,0.003644166,0.001799192,0.0004495799],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9845092,0.0003258243,0.007183551,0.005425913,0.001190741,0.0004239413,0.00009876458,0.00006144603,0.0007805978],"genre_scores_gemma":[0.9488544,0.00001694805,0.05073144,0.0001691704,0.0001069874,0.000006485235,0.000001827732,0.000009406017,0.0001032949],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6076563,"threshold_uncertainty_score":0.6342094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06367141838380903,"score_gpt":0.2462683893208179,"score_spread":0.1825969709370088,"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."}}