{"id":"W2377649834","doi":"","title":"The Application of a Improved LMS Filter on DCG De-noising","year":2011,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Adaptive Filtering Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Adaptive filter; Least mean squares filter; Filter (signal processing); Convergence (economics); Algorithm; Preprocessor; Kernel adaptive filter; Digital filter; Control theory (sociology); Artificial intelligence; Computer vision","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003341887,0.0003815386,0.0003913321,0.0003404173,0.000187226,0.0002771536,0.000369232,0.0007559068,0.001526608],"category_scores_gemma":[0.001198152,0.0001382944,0.0002437587,0.0004278276,0.0002264264,0.0003322591,0.0002257209,0.000380222,0.0004905015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002038363,"about_ca_system_score_gemma":0.0002869102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001324088,"about_ca_topic_score_gemma":0.001829293,"domain_scores_codex":[0.999731,0.00004341107,0.00001541729,0.00006790332,0.0001243794,0.00001785298],"domain_scores_gemma":[0.9996612,0.0001295764,0.00001810716,0.00003369761,0.00014558,0.00001174556],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000379286,0.00004802704,0.0008138822,0.0002192953,0.00004848036,0.0003007972,0.00007542777,0.02178668,0.4436344,0.002979924,0.001276609,0.5284372],"study_design_scores_gemma":[0.00009998701,0.0007479951,0.007860141,0.00007153304,0.0001807456,0.001350471,0.00005272997,0.6106293,0.3358654,0.001788487,0.04126852,0.00008473374],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03185214,0.001299271,0.96195,0.0002921364,0.0001896539,0.00006851896,0.00004188108,0.0004938501,0.003812581],"genre_scores_gemma":[0.3982431,0.002415942,0.5885093,0.0002596399,0.0002704957,0.000112724,0.0001180954,0.00008611025,0.009984564],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001526608,"threshold_uncertainty_score":0.005106986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01290503000234089,"score_gpt":0.2235364414450851,"score_spread":0.2106314114427442,"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."}}