{"id":"W2490018496","doi":"10.1109/ccece.1997.608287","title":"A generic processing structure decomposing the beamforming process of 2-D and 3-D arrays of sensors into sub-sets of coherent processes","year":2002,"lang":"en","type":"article","venue":"","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Technical University of Nova Scotia","funders":"","keywords":"Beamforming; Adaptive beamformer; Planar; Process (computing); Computer science; WSDMA; Planar array; Electronic engineering; Implementation; Algorithm; Topology (electrical circuits); Engineering; MIMO; Telecommunications; Electrical engineering; Precoding","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":[0.0001674032,0.0002076802,0.000363894,0.0001391406,0.0001803185,0.00008698749,0.0006174216,0.00006861638,0.000009634868],"category_scores_gemma":[0.00009782089,0.0001353357,0.00004207974,0.001015849,0.0002328845,0.0006535363,0.0001426871,0.0001233103,2.285718e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001530226,"about_ca_system_score_gemma":0.0001287499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001787297,"about_ca_topic_score_gemma":0.0000294164,"domain_scores_codex":[0.9984504,0.00003017447,0.0005357389,0.0003400372,0.0003749226,0.0002687237],"domain_scores_gemma":[0.998502,0.0000921582,0.0005996531,0.0002826421,0.0004561989,0.00006734737],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000224357,0.0001910167,0.006311968,0.006430635,0.00005775045,0.000003741455,0.02543969,0.003401,0.4944674,0.0001290136,0.00003925201,0.463506],"study_design_scores_gemma":[0.0002441188,0.00008370981,0.000231448,0.000390779,0.00001991167,0.00004999407,0.0007002238,0.04063418,0.9556992,0.001761927,0.00001600462,0.000168493],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9309244,0.002649079,0.06569654,0.000180567,0.00003324592,0.0002033248,0.000001901538,0.00004582636,0.0002651053],"genre_scores_gemma":[0.9165744,0.00006375871,0.08326902,0.00004659909,0.00001959884,0.000004806928,6.652806e-7,0.00001223829,0.000008927625],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4633376,"threshold_uncertainty_score":0.5518829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0158455655213708,"score_gpt":0.2487256593688379,"score_spread":0.2328800938474672,"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."}}