{"id":"W2122053456","doi":"","title":"A cross-relation based affine projection algorithm for blind SIMO system identification","year":2011,"lang":"en","type":"article","venue":"","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"","keywords":"Algorithm; Affine transformation; Computational complexity theory; Rate of convergence; Projection (relational algebra); Convergence (economics); Mathematics; Adaptive filter; Computer science; Relation (database); System identification; Mathematical optimization; Data modeling; Channel (broadcasting)","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":[0.0008743165,0.0008705449,0.0005436479,0.0006686316,0.0004556526,0.0007755791,0.0009359894,0.000806891,0.002721749],"category_scores_gemma":[0.00210857,0.0003449995,0.0005625917,0.0008911662,0.0007481527,0.001097274,0.0009192764,0.001608995,0.001250727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003477423,"about_ca_system_score_gemma":0.001020298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001248531,"about_ca_topic_score_gemma":0.001328233,"domain_scores_codex":[0.9993968,0.0001569831,0.00003101051,0.0001344076,0.0002497302,0.00003111182],"domain_scores_gemma":[0.9993144,0.0002510238,0.00007574802,0.0001122779,0.0002208449,0.00002560115],"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":[0.0002472547,0.00009324218,0.0007707343,0.0001969039,0.0001227753,0.000107886,0.0001449081,0.1407219,0.05410328,0.03000649,0.003310445,0.7701742],"study_design_scores_gemma":[0.00001644187,0.0001051633,0.0003927583,0.00001130295,0.00001843958,0.0001900938,0.00001083468,0.975691,0.01567733,0.002354834,0.005500607,0.00003129489],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001438494,0.0001065678,0.9977797,0.00002212504,0.00002057166,0.0000143962,0.000007777294,0.0001871418,0.000423397],"genre_scores_gemma":[0.05507731,0.0002888442,0.9417477,0.0000665773,0.00005590365,0.0001106387,0.00009514864,0.00007532032,0.002482519],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002721749,"threshold_uncertainty_score":0.009105206,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04949023430120057,"score_gpt":0.3038041116673278,"score_spread":0.2543138773661272,"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."}}