{"id":"W1942115824","doi":"10.1109/pacrim.1993.407151","title":"Noise cancellation using nonlinear adaptive FIR digital filters","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Adaptive Filtering Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Adaptive filter; Finite impulse response; Digital filter; Computer science; Root-raised-cosine filter; Nonlinear filter; Filter (signal processing); Nonlinear system; Noise (video); Kernel adaptive filter; Filter design; Active noise control; Control theory (sociology); Algorithm; Mathematics; Artificial intelligence; Physics; Computer vision","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00001581688,0.0001489611,0.0001139605,0.00006487464,0.00003626643,0.00003421347,0.0000876599,0.00004937602,0.0002261063],"category_scores_gemma":[0.00001005936,0.0001547717,0.00004029829,0.0001224778,0.0000287518,0.0004203434,0.00003009745,0.00009989267,0.00006063397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001489955,"about_ca_system_score_gemma":0.000002447003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009495563,"about_ca_topic_score_gemma":0.000003907753,"domain_scores_codex":[0.9994039,0.000003702266,0.0001431072,0.0001459471,0.00009963802,0.0002037214],"domain_scores_gemma":[0.9997085,0.00002253021,0.00002088412,0.0001652859,0.00002876015,0.00005399388],"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":[0.00002343445,0.00007319086,0.0005843774,0.0000648881,0.0001017473,0.00004513101,0.0005257673,0.8189482,0.09174272,0.0006919932,0.006994165,0.08020438],"study_design_scores_gemma":[0.0001008837,0.00002995953,0.00008388064,0.00003031029,0.000004046045,0.000006734272,0.00002409926,0.974923,0.01702577,0.0001541696,0.007385011,0.0002321621],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09383693,0.0001422313,0.8669712,0.00002101417,0.0001874559,0.0002252991,0.00006049409,0.002036799,0.03651861],"genre_scores_gemma":[0.8665097,0.00002330897,0.1326753,0.00001931788,0.00009585186,0.000006396011,0.000006244347,0.00004353495,0.0006203627],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7726728,"threshold_uncertainty_score":0.6311407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03535166072535448,"score_gpt":0.2221642458321475,"score_spread":0.186812585106793,"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."}}