{"id":"W2905357467","doi":"10.3390/a11120211","title":"A Connection Between the Kalman Filter and an Optimized LMS Algorithm for Bilinear Forms","year":2018,"lang":"en","type":"article","venue":"Algorithms","topic":"Advanced Adaptive Filtering Techniques","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"Strong","keywords":"Kalman filter; Bilinear interpolation; Algorithm; Adaptive filter; Computer science; Identification (biology); System identification; Finite impulse response; Wiener filter; Context (archaeology); Least mean squares filter; Impulse (physics); Connection (principal bundle); Mathematics; Control theory (sociology); Artificial intelligence; Data mining","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":[0.001060556,0.0007701222,0.0006212957,0.0006176499,0.0002943978,0.0007487165,0.0005986342,0.001016739,0.002290512],"category_scores_gemma":[0.004326567,0.0003739182,0.0005976275,0.0007488921,0.000937315,0.001809169,0.0008227249,0.001465383,0.0006732065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004490836,"about_ca_system_score_gemma":0.0008088254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001592883,"about_ca_topic_score_gemma":0.0009935608,"domain_scores_codex":[0.9993449,0.0001858642,0.00006534329,0.000184145,0.0001773043,0.00004252861],"domain_scores_gemma":[0.9990634,0.0005214413,0.0001230566,0.0001052196,0.0001650059,0.00002194965],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001198128,0.00005032205,0.000876388,0.0003572299,0.0001002111,0.0001394533,0.0002827264,0.3903547,0.01845657,0.2918559,0.001542489,0.2958641],"study_design_scores_gemma":[0.00001426628,0.00009648562,0.0003590487,0.00004133837,0.00002351215,0.0001395352,0.00001988512,0.9248719,0.00573097,0.05861345,0.01004768,0.0000420091],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0008440276,0.0001629235,0.9983392,0.00005241071,0.00003066738,0.000006940408,0.000006826638,0.00004872495,0.0005083385],"genre_scores_gemma":[0.2381111,0.002166766,0.7533031,0.0001785267,0.0002891845,0.0001581638,0.00009757365,0.0001253087,0.005570149],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002290512,"threshold_uncertainty_score":0.007662535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02755374483367571,"score_gpt":0.2862493122813546,"score_spread":0.2586955674476789,"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."}}