{"id":"W2088652862","doi":"10.1049/iet-spr.2008.0203","title":"Least square identification of alias components of linear periodically time-varying systems and optimal training signal design","year":2010,"lang":"en","type":"article","venue":"IET Signal Processing","topic":"Advanced Adaptive Filtering Techniques","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Alias; Control theory (sociology); Finite impulse response; Oversampling; Infinite impulse response; Mathematics; Algorithm; Computer science; Digital filter; Filter (signal processing); Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003991257,0.0002034955,0.0003405451,0.0001369943,0.0001147393,0.00005960693,0.0001886297,0.000125096,0.00001893027],"category_scores_gemma":[0.00003050269,0.0002168921,0.0000431842,0.0001553859,0.0001781121,0.0003788464,0.0000422071,0.0002974976,0.000002494857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002299242,"about_ca_system_score_gemma":0.00003810067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006109143,"about_ca_topic_score_gemma":1.740238e-7,"domain_scores_codex":[0.9986466,0.00003853777,0.0005727321,0.0002324245,0.0002779911,0.0002317489],"domain_scores_gemma":[0.9993084,0.00007914726,0.0002332329,0.0001334985,0.0001675001,0.00007820326],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003492778,0.00001969297,0.00005595365,0.0005401049,0.00001808572,0.000003199389,0.0009291993,0.09973826,0.8890355,0.00001938752,0.000005664258,0.009600068],"study_design_scores_gemma":[0.0002064931,0.00006734795,0.0002558865,0.000518901,0.0000221875,0.00002818929,0.0001320448,0.7694632,0.2290072,0.00006282814,0.00003190624,0.0002038091],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3271699,0.0002207187,0.6720576,0.000004411907,0.00004274802,0.0001903918,0.00001668996,0.0002301569,0.00006746444],"genre_scores_gemma":[0.9173682,0.000004241282,0.08245502,0.000002192203,0.00007169802,0.00001908969,0.00001342794,0.00005059077,0.00001550673],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.669725,"threshold_uncertainty_score":0.8844602,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03735958056389142,"score_gpt":0.2624396709400343,"score_spread":0.2250800903761429,"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."}}