{"id":"W2135655162","doi":"10.1109/icccn.2009.5235221","title":"Adaptive Downsampling in Oversampled Filter Banks in the Presence of Quantization Noise","year":2009,"lang":"en","type":"article","venue":"","topic":"Digital Filter Design and Implementation","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Upsampling; Polyphase system; Algorithm; Quantization (signal processing); Filter bank; Mathematics; Computer science; Finite impulse response; Redundancy (engineering); Adaptive filter; Control theory (sociology); Channel (broadcasting); Electronic engineering; 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":[0.0002875354,0.00006342927,0.00007910963,0.0001212625,0.00001470694,0.00008499627,0.0004116619,0.00001870414,0.00001397129],"category_scores_gemma":[0.00004227669,0.00004563954,0.00002120954,0.0005103415,0.00001163751,0.0009491225,0.00003326974,0.00004968508,0.000004570151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001745006,"about_ca_system_score_gemma":0.00002115882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001372024,"about_ca_topic_score_gemma":0.00008387714,"domain_scores_codex":[0.9992071,0.00006530228,0.0002303157,0.0001650057,0.0001940869,0.0001382236],"domain_scores_gemma":[0.9995299,0.0001564152,0.00005588104,0.0002130287,0.00003086081,0.00001391814],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00007985869,0.0004463898,0.009956549,0.00001434026,0.000007049158,0.00001357739,0.01771887,0.003932817,0.01133634,0.7896468,0.001340969,0.1655065],"study_design_scores_gemma":[0.001583826,0.0006516202,0.4944363,0.00009616725,0.000003416898,0.000006062397,0.0008731504,0.4348313,0.01171716,0.05519076,0.0002844376,0.0003258417],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05523695,0.000009811772,0.9373098,0.000589854,0.00004061962,0.0002661689,0.000002011627,0.00001896747,0.006525781],"genre_scores_gemma":[0.9835572,0.000003012208,0.01583345,0.0005567991,0.000006507902,0.000005106209,0.000004428437,0.000001370276,0.00003216747],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9283202,"threshold_uncertainty_score":0.1861127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05156478851187114,"score_gpt":0.2905825390037907,"score_spread":0.2390177504919196,"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."}}