{"id":"W2038253873","doi":"10.1016/s0165-1684(02)00135-4","title":"Numerically stable fast convergence least-squares algorithms for multichannel active sound cancellation systems and sound deconvolution systems","year":2002,"lang":"en","type":"article","venue":"Signal Processing","topic":"Advanced Adaptive Filtering Techniques","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Algorithm; QR decomposition; Recursive least squares filter; Adaptive filter; System identification; Deconvolution; Computer science; Convergence (economics); Active noise control; Numerical stability; Mathematics; Numerical analysis; Filter (signal processing)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000119839,0.0002499524,0.0002778901,0.00009383882,0.0002518741,0.0001736173,0.000104453,0.0001067705,0.000009701285],"category_scores_gemma":[0.00002253957,0.0002661485,0.00003164933,0.0001547889,0.00007737063,0.0006800634,0.00002515701,0.0001463648,0.000005126511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000274586,"about_ca_system_score_gemma":0.00001355291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006085183,"about_ca_topic_score_gemma":0.000007087899,"domain_scores_codex":[0.9987544,0.00002579572,0.0003166879,0.0003291903,0.0001858415,0.0003881098],"domain_scores_gemma":[0.9993709,0.00008872108,0.0001334918,0.0001060762,0.0002071345,0.0000936286],"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":[0.00007501084,0.00005200576,0.0003201085,0.002984964,0.00009922641,0.000006473081,0.002435682,0.8832646,0.04952941,0.0004138627,0.0002029074,0.06061576],"study_design_scores_gemma":[0.0002617353,0.00007718201,0.00005122964,0.0002746798,0.00002087775,0.00001671986,0.0007932507,0.9941248,0.002936905,0.0007445716,0.0003715661,0.000326532],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0185649,0.004991315,0.9747154,0.000005892519,0.0002682572,0.0006405999,0.00005958477,0.0005564333,0.000197621],"genre_scores_gemma":[0.9894365,0.00005352834,0.009837623,0.000004689196,0.0002159654,0.0002255998,0.00001246227,0.00006471584,0.0001489071],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9708716,"threshold_uncertainty_score":0.9999791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04014026377143567,"score_gpt":0.2607476609620002,"score_spread":0.2206073971905645,"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."}}