{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006535598,0.0005601947,0.0005055163,0.0006931892,0.0006117588,0.0009059289,0.0005271583,0.001475808,0.00247463],"category_scores_gemma":[0.002741642,0.0002710153,0.0008545532,0.0006749005,0.001069341,0.0009155035,0.0008941316,0.001040576,0.0007767281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003891354,"about_ca_system_score_gemma":0.000388539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001642391,"about_ca_topic_score_gemma":0.0009251561,"domain_scores_codex":[0.9995227,0.00008335918,0.00004157496,0.0001167043,0.0001790869,0.00005653272],"domain_scores_gemma":[0.9991865,0.0003415695,0.0001493047,0.0001060005,0.000186902,0.00002987017],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001643435,0.00004180965,0.002367405,0.000417718,0.0000718441,0.0007685264,0.000767404,0.2108078,0.0192245,0.5764974,0.002994161,0.1858771],"study_design_scores_gemma":[0.00003819003,0.0001697297,0.003217018,0.0001191857,0.00005404216,0.00124767,0.0002063252,0.6646628,0.01981872,0.2710397,0.03929788,0.0001287265],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01519038,0.00103727,0.9692563,0.0002262566,0.00005517296,0.00003215958,0.00008719366,0.0003752247,0.01374006],"genre_scores_gemma":[0.6831427,0.002021553,0.3059064,0.0001419358,0.00009507307,0.0001671585,0.0002352753,0.0001504965,0.008139541],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00247463,"threshold_uncertainty_score":0.008278489,"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."}}