{"id":"W1597266963","doi":"10.5281/zenodo.38304","title":"Echo Cancellation Using A Variable Step-Size Nlms Algorithm","year":2004,"lang":"en","type":"article","venue":"INFM-OAR (INFN Catania)","topic":"Advanced Adaptive Filtering Techniques","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Convergence (economics); Echo (communications protocol); Variable (mathematics); Least mean squares filter; Algorithm; Residual; Computer science; Adaptive filter; Scheme (mathematics); Mathematics","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":[0.0008818069,0.0007756452,0.0006328542,0.0006963322,0.0004116893,0.0008466041,0.0007992933,0.001464459,0.004148455],"category_scores_gemma":[0.003438073,0.0003497127,0.0005674677,0.0007309407,0.0004560337,0.001325628,0.0007527827,0.001264653,0.002271554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002959469,"about_ca_system_score_gemma":0.0007926777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009060787,"about_ca_topic_score_gemma":0.00216579,"domain_scores_codex":[0.9994281,0.0001773343,0.00003715732,0.00008423703,0.0002421139,0.0000310287],"domain_scores_gemma":[0.99892,0.0006493899,0.00004682548,0.0001404284,0.0002131791,0.00003028532],"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":[0.001063884,0.0001925147,0.0005597021,0.0002663747,0.000177221,0.0001801403,0.0001758036,0.07083694,0.2008871,0.02590473,0.00486588,0.6948897],"study_design_scores_gemma":[0.000144977,0.0001373143,0.0005417371,0.00003008138,0.0000694521,0.0002823954,0.00001842644,0.9235125,0.05784164,0.005991901,0.01138734,0.00004219588],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002666221,0.0001231261,0.9959091,0.0000867733,0.00008731287,0.00001813678,0.00001816964,0.0003245599,0.0007665817],"genre_scores_gemma":[0.04572023,0.0002294779,0.9483821,0.000131156,0.00009048367,0.00008676008,0.0001493599,0.0001026081,0.005107781],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004148455,"threshold_uncertainty_score":0.01387799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01335282652974451,"score_gpt":0.2344950045888709,"score_spread":0.2211421780591264,"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."}}