{"id":"W4213363428","doi":"10.1109/lsp.2022.3152108","title":"Joint Parameter and Time-Delay Estimation for a Class of Nonlinear Time-Series Models","year":2022,"lang":"en","type":"article","venue":"IEEE Signal Processing Letters","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":142,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Higher Education Discipline Innovation Project; National Natural Science Foundation of China","keywords":"Nonlinear system; Autoregressive model; Computer science; Series (stratigraphy); Estimation theory; Time series; Nonlinear autoregressive exogenous model; Algorithm; Identification (biology); Mathematical optimization; Control theory (sociology); Mathematics; Artificial intelligence; Machine learning; Statistics; Control (management)","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":[0.001029792,0.000705954,0.0006527263,0.0004543544,0.0002283884,0.0005566751,0.0005493202,0.0005984899,0.0004666223],"category_scores_gemma":[0.003571659,0.0002676895,0.0006271564,0.0005254213,0.0004468068,0.001279964,0.0006845568,0.001253773,0.0001538284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002949048,"about_ca_system_score_gemma":0.0005957019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002105724,"about_ca_topic_score_gemma":0.001774966,"domain_scores_codex":[0.9996517,0.0000767356,0.00002660877,0.0001091086,0.0001054739,0.00003046724],"domain_scores_gemma":[0.999038,0.0005592016,0.0001540489,0.0001149399,0.0001107797,0.00002309234],"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":[0.0001088129,0.00005973759,0.002140265,0.0001246313,0.0001001761,0.000111542,0.00008828349,0.8179752,0.01164179,0.02660486,0.0006204918,0.1404242],"study_design_scores_gemma":[0.000001584236,0.000009480013,0.0001501626,0.000001638824,0.00000394115,0.0000159066,0.000002625377,0.9972063,0.0007493378,0.00165638,0.0001992132,0.0000035],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01598782,0.0001387709,0.983478,0.0000433126,0.00001664571,0.000006196978,0.0000154332,0.0000639996,0.0002497133],"genre_scores_gemma":[0.7718387,0.0007407548,0.2247951,0.00004493875,0.00008759907,0.00005905747,0.000192982,0.00005345247,0.002187538],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002105724,"threshold_uncertainty_score":0.005446136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01215193104042406,"score_gpt":0.2083848560866763,"score_spread":0.1962329250462522,"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."}}