{"id":"W2038068522","doi":"10.3182/20050703-6-cz-1902.00010","title":"ON THE HERMITE SERIES APPROACH TO NONPARAMETRIC IDENTIFICATION OF HAMMERSTEIN SYSTEMS","year":2005,"lang":"en","type":"article","venue":"IFAC Proceedings Volumes","topic":"Control Systems and Identification","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University; Université de Montréal; Concordia University","funders":"","keywords":"Parameterized complexity; Nonparametric statistics; Convergence (economics); Identification (biology); Series (stratigraphy); Nonlinear system; Hermite polynomials; Mathematics; Control theory (sociology); System identification; Mathematical optimization; Applied mathematics; Nonlinear system identification; Computer science; Algorithm; Data modeling; Artificial intelligence; Econometrics","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":[0.004089942,0.0009231854,0.001198076,0.001209971,0.000530486,0.001429731,0.001174657,0.001367029,0.002181548],"category_scores_gemma":[0.01322071,0.0006352542,0.000945184,0.001379826,0.002283989,0.002469062,0.001370499,0.002972787,0.0004712689],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008001434,"about_ca_system_score_gemma":0.0008449269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003514745,"about_ca_topic_score_gemma":0.003289229,"domain_scores_codex":[0.998794,0.0006706489,0.00005534463,0.0001370752,0.0002807576,0.00006218685],"domain_scores_gemma":[0.9946302,0.004338257,0.0002094786,0.0003108149,0.0004297293,0.00008150538],"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":[0.00006316693,0.000049714,0.0003773252,0.0001196273,0.00005799488,0.0001110576,0.0001598906,0.284536,0.001854956,0.6538774,0.001861752,0.05693107],"study_design_scores_gemma":[0.000005819196,0.00002379433,0.0002048921,0.00001820092,0.00001037968,0.00003590562,0.00001789648,0.7101969,0.0003762531,0.2869069,0.002179632,0.00002347938],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00540334,0.0009157242,0.9900165,0.0002692037,0.00009053539,0.00001063987,0.00002596862,0.00006398294,0.003204162],"genre_scores_gemma":[0.5477322,0.009628404,0.4010396,0.0006392359,0.001897101,0.0002161815,0.0003881757,0.0004006432,0.03805852],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004089942,"threshold_uncertainty_score":0.02162993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008928781776166446,"score_gpt":0.1912255376297242,"score_spread":0.1822967558535577,"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."}}