{"id":"W2131697078","doi":"10.1109/wpmc.2002.1088382","title":"Oversampled filter banks as error correcting codes","year":2003,"lang":"en","type":"article","venue":"","topic":"Digital Filter Design and Implementation","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Oversampling; Subspace topology; Polyphase system; Linear subspace; Filter bank; Projection (relational algebra); Filter (signal processing); Algorithm; Noise (video); Computer science; Mathematics; Speech recognition; Image (mathematics); Artificial intelligence; Telecommunications; Electronic engineering; Computer vision; Pure mathematics; Engineering","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":[0.0004521083,0.0003748716,0.0003132605,0.0006253335,0.0002665724,0.001027515,0.0004862568,0.0006965681,0.001827452],"category_scores_gemma":[0.002498982,0.0002342519,0.0002861564,0.0007020299,0.001244793,0.001251658,0.0005410557,0.0009416541,0.0005172621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005728616,"about_ca_system_score_gemma":0.0005249848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006440495,"about_ca_topic_score_gemma":0.0007130485,"domain_scores_codex":[0.9993469,0.0001486639,0.00002809169,0.00009223348,0.0003310501,0.00005294897],"domain_scores_gemma":[0.9989524,0.0004397956,0.0001394494,0.0002135358,0.0002327773,0.00002203563],"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":[0.00007200879,0.00001165217,0.0003063084,0.00008809812,0.00001721933,0.0001760861,0.0001933788,0.05212865,0.0174552,0.8499167,0.001000741,0.07863402],"study_design_scores_gemma":[0.00003163103,0.000109314,0.000600604,0.0001324185,0.00003864203,0.001009571,0.00008916741,0.443566,0.04656367,0.4617861,0.04600949,0.00006348874],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02906779,0.001579278,0.9599802,0.0002711437,0.0002128069,0.00002899542,0.0000839859,0.0003526022,0.008423104],"genre_scores_gemma":[0.5075125,0.003927958,0.472459,0.0005206013,0.0004843458,0.0001056913,0.0001654599,0.000187695,0.01463672],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001827452,"threshold_uncertainty_score":0.00611341,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04448024143271988,"score_gpt":0.294896787629717,"score_spread":0.2504165461969972,"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."}}