{"id":"W2127567620","doi":"10.1109/wcsp.2009.5371541","title":"Whitening-rotation-based semi-blind estimation of MIMO FIR channels","year":2009,"lang":"en","type":"article","venue":"","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"MIMO; Finite impulse response; Algorithm; Impulse (physics); Channel (broadcasting); Computer science; Rotation (mathematics); Matrix (chemical analysis); Impulse response; Mathematics; Control theory (sociology); Artificial intelligence; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003000306,0.00009210272,0.0001181335,0.0001916034,0.00004794345,0.00009180535,0.0003554062,0.00006350435,0.00002762586],"category_scores_gemma":[0.00006295995,0.00008617273,0.00004721087,0.0004549714,0.0000177268,0.000466703,0.00001988475,0.0000674714,0.00001778097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001663721,"about_ca_system_score_gemma":0.00007237179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000109025,"about_ca_topic_score_gemma":0.000001914931,"domain_scores_codex":[0.9991195,0.00004959182,0.0002607386,0.0002026746,0.0002465273,0.0001209226],"domain_scores_gemma":[0.9992503,0.00008288207,0.0001358544,0.0003338743,0.0001510012,0.00004612198],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006277087,0.0006212959,0.0003777528,0.00004953265,0.00002366798,0.000005852395,0.005277918,0.3503937,0.01187867,0.3828914,0.01236343,0.2360541],"study_design_scores_gemma":[0.0003174456,0.0001643929,0.0008785616,0.00002049314,0.000002123665,0.000001251908,0.000009504995,0.8775579,0.1092768,0.01151104,0.000152756,0.0001077493],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02202737,0.00001089131,0.9695053,0.003498157,0.00005073244,0.000207746,5.89906e-7,0.0003971681,0.00430206],"genre_scores_gemma":[0.7428417,6.340276e-7,0.255793,0.001133809,0.00001154234,0.000008299756,0.000006646873,0.000002916516,0.0002014205],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7208143,"threshold_uncertainty_score":0.3514022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01878609767296934,"score_gpt":0.2851169270232899,"score_spread":0.2663308293503206,"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."}}