{"id":"W2056243559","doi":"10.1109/icassp.2010.5495873","title":"A variable step-size normalized sign algorithm for acoustic echo cancelation","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Adaptive Filtering Techniques","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"","keywords":"Sign (mathematics); Algorithm; Echo (communications protocol); Computer science; Variable (mathematics); Rate of convergence; A priori and a posteriori; Convergence (economics); Speech recognition; Mathematics; Telecommunications","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":[0.001089275,0.0006972273,0.0007274218,0.0008009551,0.0003671121,0.0008457514,0.001275091,0.000838873,0.002438415],"category_scores_gemma":[0.003849958,0.0003406016,0.0005311195,0.0007338001,0.0006229289,0.001231608,0.0007520972,0.001129609,0.001473785],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000318969,"about_ca_system_score_gemma":0.001365528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009384749,"about_ca_topic_score_gemma":0.001672996,"domain_scores_codex":[0.9992867,0.0001912568,0.00005965277,0.0001007527,0.0003296022,0.00003196179],"domain_scores_gemma":[0.9984398,0.0004616271,0.000119383,0.0001940224,0.0007149426,0.00007016109],"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":[0.0004158153,0.0001448385,0.001191505,0.0001460508,0.00009368045,0.00008809323,0.000076177,0.05475964,0.08853187,0.02199241,0.003524038,0.8290359],"study_design_scores_gemma":[0.00005346214,0.000141086,0.0003371244,0.00001502934,0.00002815352,0.0002671754,0.00001594594,0.9572296,0.03279904,0.002647906,0.006431016,0.00003450715],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002273053,0.0000574984,0.9969335,0.00003459434,0.00005734315,0.00002183717,0.000009620619,0.0002686962,0.0003438446],"genre_scores_gemma":[0.05627223,0.0001219098,0.9412202,0.0000538988,0.00004650587,0.0001350691,0.00008298256,0.00008657506,0.001980626],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002438415,"threshold_uncertainty_score":0.008157372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007267137318308293,"score_gpt":0.2315948781838273,"score_spread":0.224327740865519,"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."}}