{"id":"W3034200033","doi":"10.1007/s00034-020-01460-4","title":"An Optimization Framework for the Design of Noise Shaping Loop Filters with Improved Stability Properties","year":2020,"lang":"en","type":"article","venue":"Circuits Systems and Signal Processing","topic":"Advanced Adaptive Filtering Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Transfer function; Semidefinite programming; Control theory (sociology); Robustness (evolution); Kalman filter; Stability (learning theory); Norm (philosophy); Lemma (botany); Mathematics; Delta-sigma modulation; Computer science; Mathematical optimization; Bandwidth (computing); Engineering; Control (management); 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":[0.0002042453,0.0001554518,0.000218505,0.00002360318,0.0001367787,0.0001242545,0.0001363352,0.0000653422,0.000001691621],"category_scores_gemma":[0.0000452328,0.0001046126,0.00001765939,0.0001264861,0.00008002435,0.0004111007,0.00001280583,0.0001195491,5.053893e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002788999,"about_ca_system_score_gemma":0.00003198014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004422925,"about_ca_topic_score_gemma":1.829795e-7,"domain_scores_codex":[0.999243,0.00003134081,0.000242455,0.0002113908,0.0001046025,0.0001672536],"domain_scores_gemma":[0.9994839,0.00009350127,0.00009596082,0.0001177096,0.0001462177,0.00006273537],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003641857,0.000006717329,0.00004234807,0.001442831,0.00001892505,3.020259e-7,0.001468893,0.8165981,0.1710446,0.00006685533,0.000001310231,0.009272723],"study_design_scores_gemma":[0.0001234985,0.0002077419,0.00001420817,0.0005722997,0.00002115291,0.000002555014,0.0007703079,0.9664279,0.03163758,0.00006266823,0.000006587935,0.0001535046],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007479668,0.001976845,0.9893042,0.00002124839,0.00002242533,0.0008913539,0.000008294808,0.0002878339,0.000008126896],"genre_scores_gemma":[0.9493033,0.0000132448,0.05040315,0.00002044026,0.00007379508,0.0001405782,0.000001824296,0.00004279954,8.232252e-7],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9418237,"threshold_uncertainty_score":0.4265978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08199253099546457,"score_gpt":0.2461026297488784,"score_spread":0.1641100987534138,"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."}}