{"id":"W2140060717","doi":"10.1109/icassp.1995.480505","title":"A robust variable step size LMS-type algorithm: analysis and simulations","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Adaptive Filtering Techniques","field":"Engineering","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Convergence (economics); Algorithm; Variable (mathematics); Gaussian; Computer science; Noise (video); Least mean squares filter; Control theory (sociology); Gaussian noise; Steady state (chemistry); Mathematics; Adaptive filter; Artificial intelligence","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":[0.0008016633,0.0003676959,0.000573869,0.0003410479,0.0002215201,0.0004043599,0.00057318,0.001007515,0.001650787],"category_scores_gemma":[0.002413224,0.0001894136,0.0002274672,0.0004533532,0.0003374291,0.0005356069,0.0003488766,0.0004052283,0.0003936182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004201162,"about_ca_system_score_gemma":0.0004484723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003481308,"about_ca_topic_score_gemma":0.001850355,"domain_scores_codex":[0.9997848,0.00006744943,0.00001270034,0.00002238634,0.0000954325,0.00001721468],"domain_scores_gemma":[0.9991825,0.0004855105,0.00007004975,0.00005510405,0.0001896891,0.00001712104],"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":[0.00007251376,0.00002152769,0.0004127848,0.00005589606,0.00001915077,0.0000439298,0.00002152399,0.9739861,0.002942635,0.003392667,0.0003431551,0.01868814],"study_design_scores_gemma":[0.000007583713,0.00002185688,0.00007239864,0.0000024031,0.000002567531,0.0000111683,0.000001943441,0.9988071,0.0005714135,0.0003027129,0.000195948,0.000003001873],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08404317,0.0004514352,0.9079727,0.0001766071,0.00003793912,0.0001111683,0.0001041315,0.0008328425,0.006270002],"genre_scores_gemma":[0.7762996,0.0003998222,0.2203129,0.0000426715,0.00001596357,0.0002278996,0.0001543876,0.00009994039,0.002446766],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003481308,"threshold_uncertainty_score":0.006922066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02386608134851147,"score_gpt":0.2215469101291569,"score_spread":0.1976808287806454,"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."}}