{"id":"W1796407367","doi":"10.1109/pacrim.1993.407337","title":"Efficient design of recursive filters satisfying prescribed magnitude and phase specifications","year":2002,"lang":"en","type":"article","venue":"","topic":"Digital Filter Design and Implementation","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Quadratic programming; Mean squared error; Constraint (computer-aided design); Algorithm; Square (algebra); Computational complexity theory; Mathematics; Quadratic equation; Linear programming; Computer science; Stability (learning theory); Mathematical optimization; Statistics","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":[0.0001048118,0.00007664358,0.0000833053,0.00009561639,0.000052271,0.0001153559,0.0002188635,0.00001414683,0.0001201707],"category_scores_gemma":[0.00002804288,0.00007095557,0.0000202748,0.0002058846,0.0000377924,0.0002467283,0.00005994565,0.00002792255,0.00002456029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001549566,"about_ca_system_score_gemma":0.000007501797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006323226,"about_ca_topic_score_gemma":3.987753e-7,"domain_scores_codex":[0.999249,0.00004480643,0.0002049376,0.0002094319,0.0001553548,0.0001364309],"domain_scores_gemma":[0.9994704,0.0001040551,0.00007030918,0.0002345725,0.00005862367,0.00006202467],"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":[0.00003024709,0.0008056732,0.0002399924,0.00004828118,0.00006495872,0.0000119395,0.01037354,0.00193468,0.06839281,0.2053965,0.01654399,0.6961574],"study_design_scores_gemma":[0.002795908,0.0007720778,0.00257043,0.00004845875,0.00002292602,0.00002592948,0.0003929709,0.9411083,0.04612946,0.004538608,0.001187506,0.0004073849],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008399133,0.00006547596,0.9854963,0.0003931614,0.00006077089,0.0002899386,0.000006662526,0.00005053929,0.005238012],"genre_scores_gemma":[0.7688336,0.00001850012,0.2306519,0.00007990875,0.00001100065,0.00001417428,0.000002570321,0.00000417233,0.0003841693],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9391736,"threshold_uncertainty_score":0.2893484,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1505905479328893,"score_gpt":0.2922409277936122,"score_spread":0.1416503798607229,"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."}}