{"id":"W4243520243","doi":"10.32920/ryerson.14648397","title":"Online LTI system identification and time delay estimation","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Akaike information criterion; Bayesian information criterion; LTI system theory; Computer science; Model selection; Impulse response; System identification; Minimum description length; Selection (genetic algorithm); Identification (biology); Algorithm; Mathematical optimization; Control theory (sociology); Linear system; Data mining; Mathematics; Control (management); Artificial intelligence; Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006617554,0.001213858,0.001113973,0.000809475,0.0005470156,0.001285559,0.000900173,0.0008467791,0.004995551],"category_scores_gemma":[0.003571968,0.0005234897,0.0008928381,0.0009308422,0.0005707793,0.001217111,0.001216744,0.002002725,0.001895022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00080045,"about_ca_system_score_gemma":0.001485194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005817543,"about_ca_topic_score_gemma":0.00563813,"domain_scores_codex":[0.9992016,0.0001332964,0.00005428027,0.0002248748,0.0003042762,0.00008172723],"domain_scores_gemma":[0.9987651,0.0005734785,0.0002016112,0.0001818169,0.0002374277,0.00004065466],"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":[0.0002016645,0.0000837699,0.001640705,0.0003956344,0.0000940957,0.000362114,0.0002027186,0.6885287,0.01473501,0.0370903,0.003418242,0.2532471],"study_design_scores_gemma":[0.000006456054,0.00002740458,0.0003047641,0.0000130396,0.000009036417,0.00006778962,0.00001576254,0.9845383,0.002671807,0.01010539,0.002224632,0.00001554174],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002906612,0.0002523303,0.9944929,0.00007984132,0.00003920664,0.00002292581,0.0001076213,0.000556128,0.001542527],"genre_scores_gemma":[0.6051441,0.001267809,0.3790834,0.0002875275,0.0002119006,0.000329224,0.001302778,0.0003156301,0.01205772],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005817543,"threshold_uncertainty_score":0.01671177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01839854099436562,"score_gpt":0.2803714906123301,"score_spread":0.2619729496179645,"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."}}