{"id":"W2030136716","doi":"10.1109/ccece.2010.5575121","title":"Global design of perfect-reconstruction orthogonal cosine-modulated filter banks","year":2010,"lang":"en","type":"article","venue":"","topic":"Digital Filter Design and Implementation","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Recursion (computer science); Filter (signal processing); Computer science; Algorithm; Filter bank; Trigonometric functions; Finite impulse response; Mathematical optimization; Point (geometry); Adaptive filter; Filter design; Mathematics; Computer vision","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":[0.0001574057,0.0001032806,0.0001060505,0.0000587714,0.00004091328,0.0001287635,0.0003203513,0.00005159465,0.0002948628],"category_scores_gemma":[0.00001899056,0.00009037527,0.00004687019,0.0003017949,0.00004671263,0.0009021478,0.00006915049,0.00006082064,0.00003989003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001703669,"about_ca_system_score_gemma":0.00007383504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002598272,"about_ca_topic_score_gemma":0.00002166832,"domain_scores_codex":[0.9991193,0.00003584617,0.0002415145,0.0002341199,0.0001939755,0.0001751759],"domain_scores_gemma":[0.9994339,0.00003738834,0.00007902175,0.0002664537,0.0001151209,0.00006809497],"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":[0.00003595644,0.000133459,0.01252221,0.00001492382,0.00004630301,0.000005308651,0.0001273584,0.0002288195,0.1465898,0.1291416,0.005136159,0.7060182],"study_design_scores_gemma":[0.002774141,0.001033407,0.2012357,0.00004896552,0.00002989839,0.0008058246,0.00003939779,0.561421,0.1895796,0.04038627,0.001647921,0.0009979818],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1885382,0.000002075428,0.8032588,0.00009241021,0.0004655772,0.0001466331,0.000008329357,0.00008915651,0.007398814],"genre_scores_gemma":[0.8948083,5.374443e-7,0.1048579,0.0001244408,0.00002916569,0.000004913233,0.000007909387,0.000003375342,0.000163501],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.70627,"threshold_uncertainty_score":0.3685397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02090499278738207,"score_gpt":0.2583487347151238,"score_spread":0.2374437419277418,"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."}}