{"id":"W2025396508","doi":"10.1049/el.2010.2498","title":"Adaptive beamforming with joint robustness against covariance matrix uncertainty and signal steering vector mismatch","year":2010,"lang":"en","type":"article","venue":"Electronics Letters","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Adaptive beamformer; Covariance matrix; Robustness (evolution); Control theory (sociology); Diagonal; Beamforming; Covariance; Algorithm; Mathematics; Diagonal matrix; Computer science; Estimation of covariance matrices; Matrix (chemical analysis); Mathematical optimization; Statistics; Artificial intelligence","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":[0.001171802,0.000977267,0.0009981428,0.0004714981,0.0003754592,0.0009213845,0.001243777,0.001160918,0.0009999212],"category_scores_gemma":[0.005164129,0.000663604,0.0006941292,0.0009247154,0.0006475692,0.001475521,0.001427499,0.001330492,0.0006986068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004013542,"about_ca_system_score_gemma":0.0009987639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00145693,"about_ca_topic_score_gemma":0.001541916,"domain_scores_codex":[0.9986609,0.0002690553,0.00009513025,0.0002548876,0.0006296597,0.00009030343],"domain_scores_gemma":[0.9983027,0.0007801143,0.0002353849,0.000176723,0.0004588506,0.00004612924],"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":[0.000274357,0.00005109804,0.0006597539,0.0001277706,0.0001361101,0.0001026339,0.0001042114,0.5251354,0.06667303,0.02083672,0.002080095,0.3838189],"study_design_scores_gemma":[0.00002130127,0.00007160367,0.0002785858,0.000008532043,0.00001871294,0.0001114706,0.000005781075,0.9832259,0.0103198,0.0041265,0.001783837,0.00002807224],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001650705,0.00006258333,0.9978582,0.00003961936,0.00001493716,0.00000659731,0.00000743609,0.0001026937,0.0002571156],"genre_scores_gemma":[0.1894828,0.0003344556,0.8065818,0.0001324616,0.0001183358,0.0001793146,0.000170464,0.0001380605,0.002862246],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00145693,"threshold_uncertainty_score":0.006197155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007254560196589095,"score_gpt":0.2140926222556181,"score_spread":0.206838062059029,"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."}}