{"id":"W1893886650","doi":"10.1109/icassp.1981.1171369","title":"An adaptive interference canceller using Kalman filtering","year":2005,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Beamwidth; Interference (communication); Kalman filter; Computer science; Convergence (economics); Single antenna interference cancellation; SIGNAL (programming language); Antenna (radio); Adaptive filter; Algorithm; Process (computing); Control theory (sociology); Telecommunications; Artificial intelligence; Decoding methods","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":[0.0001077258,0.00007699103,0.00009166544,0.00009832651,0.00004373801,0.00005097404,0.0004830451,0.00002640689,0.00008454527],"category_scores_gemma":[0.0000096497,0.000073429,0.0000232522,0.0001897992,0.0000285796,0.001031689,0.0001076621,0.00005314532,0.00001075441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006413528,"about_ca_system_score_gemma":0.00003939938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003247251,"about_ca_topic_score_gemma":0.00006807376,"domain_scores_codex":[0.9993702,0.00002592836,0.0001707551,0.0002008636,0.0001154599,0.0001167764],"domain_scores_gemma":[0.9995008,0.00002075346,0.00007232862,0.0002690956,0.00008789498,0.00004912062],"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":[0.00001614921,0.0001780283,0.0003486873,0.00001900615,0.00002215459,0.000002965268,0.002611954,0.01234979,0.1915936,0.1272474,0.0006092989,0.6650009],"study_design_scores_gemma":[0.00003384526,0.00007846823,0.0002347338,0.00002634807,0.000001113501,0.000004414741,0.00001572681,0.6902761,0.3082289,0.0008019886,0.0002132599,0.00008510934],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03129102,0.000009010236,0.9580105,0.00005665174,0.00007471997,0.00006426565,5.155807e-7,0.0003483498,0.01014499],"genre_scores_gemma":[0.5634314,0.000001240088,0.4364241,0.00004948765,0.00001733771,0.000002879965,1.171826e-7,0.000002883936,0.00007057301],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6779264,"threshold_uncertainty_score":0.2994348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0461417763042081,"score_gpt":0.3121988001345969,"score_spread":0.2660570238303889,"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."}}