{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005137461,0.0001571648,0.0002045914,0.0001527236,0.00006225305,0.0009228431,0.0004962466,0.0002150691,0.00001020381],"category_scores_gemma":[0.00003856067,0.0001580556,0.0000493795,0.0001530687,0.00001923572,0.0004178525,0.0008759717,0.0002398926,0.00003748817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008052529,"about_ca_system_score_gemma":0.0001221661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000050978,"about_ca_topic_score_gemma":0.000009178455,"domain_scores_codex":[0.9985453,0.0001526943,0.0003903311,0.0005549412,0.0002560554,0.0001006224],"domain_scores_gemma":[0.9986032,0.00004849997,0.0002413051,0.0008280688,0.0002251866,0.00005375904],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008554187,0.0007600853,0.0001353338,0.002044325,0.0002511795,0.00007327976,0.009042948,0.0213243,0.01058037,0.6976669,0.009036876,0.2490759],"study_design_scores_gemma":[0.00004820109,0.000009261536,0.0007130819,0.0001321597,0.00001074484,0.00002945529,0.00003868105,0.9929638,0.004190876,0.001592158,0.00009472982,0.0001768749],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0197342,0.0001240323,0.9761441,0.0009402733,0.0001774993,0.0003213718,0.000006465852,0.001161246,0.001390761],"genre_scores_gemma":[0.5629363,0.00001880964,0.4355245,0.0001458794,0.00002959642,0.00003904486,0.00025063,0.00001019177,0.001045036],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9716395,"threshold_uncertainty_score":0.8898997,"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."}}