{"id":"W2773187818","doi":"10.1109/tcsi.2017.2772345","title":"Design of Least-Squares and Minimax Composite Filters","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Circuits and Systems I Regular Papers","topic":"Digital Filter Design and Implementation","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Minimax; Chebyshev filter; Stopband; Prototype filter; Finite impulse response; Control theory (sociology); Mathematics; Filter design; Network synthesis filters; Filter (signal processing); Passband; Linear phase; Least-squares function approximation; Algorithm; Computer science; Mathematical optimization; Electronic engineering; Band-pass filter; Engineering; Statistics; Artificial intelligence","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":[0.0002114168,0.0001439669,0.0002139657,0.0001058525,0.0003824636,0.0005255622,0.0003109056,0.00004942617,0.000003452825],"category_scores_gemma":[0.000004123235,0.0001308892,0.00004585032,0.0000516067,0.0001260112,0.0006244765,0.000003672642,0.0000586818,0.000002812718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001655141,"about_ca_system_score_gemma":0.00003476777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006358667,"about_ca_topic_score_gemma":0.000003133962,"domain_scores_codex":[0.9989643,0.00008468338,0.0002492397,0.0003055006,0.0002226136,0.0001736368],"domain_scores_gemma":[0.9991232,0.00007766306,0.000152739,0.0004737608,0.0000448219,0.0001277953],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004234859,0.0001675493,0.0002197907,0.0003313402,0.0002624748,0.00002476726,0.00318479,0.003190995,0.4149202,0.00572792,0.000338731,0.5715891],"study_design_scores_gemma":[0.02042734,0.009941861,0.05245702,0.004150711,0.0007403299,0.001957951,0.00530063,0.3801613,0.5028538,0.002230136,0.01370256,0.006076455],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01844777,0.0001350622,0.9791089,0.0001624416,0.0004435265,0.0003491273,0.0000209915,0.00004104316,0.001291178],"genre_scores_gemma":[0.9986464,0.00005471673,0.0006658626,0.00004802161,0.00001264375,0.00002064503,8.610785e-7,0.000009484531,0.00054132],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9801987,"threshold_uncertainty_score":0.5337505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04608496822169241,"score_gpt":0.2571673621570775,"score_spread":0.2110823939353851,"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."}}