{"id":"W2148959261","doi":"10.1109/72.896810","title":"On the use of separable Volterra networks to model discrete-time Volterra systems","year":2001,"lang":"en","type":"letter","venue":"IEEE Transactions on Neural Networks","topic":"Control Systems and Identification","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Volterra series; Volterra integral equation; Volterra equations; Separable space; Cascade; Nonlinear system; Computer science; Applied mathematics; Polynomial; Mathematical optimization; Mathematics; Control theory (sociology); Integral equation; Mathematical analysis; Artificial intelligence; Physics; 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":[0.0006775471,0.0005837999,0.0003800792,0.0002930262,0.0003105747,0.0007921551,0.0007598204,0.001688887,0.001955471],"category_scores_gemma":[0.002734883,0.0002160369,0.000274771,0.0003589174,0.0008783638,0.001556452,0.0006978037,0.001978719,0.001606183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006105536,"about_ca_system_score_gemma":0.0001866761,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001361615,"about_ca_topic_score_gemma":0.001953004,"domain_scores_codex":[0.9994949,0.0001839971,0.0000195357,0.00005515188,0.0002158606,0.00003046095],"domain_scores_gemma":[0.998969,0.0006376326,0.00004690671,0.000122917,0.0002002381,0.00002341223],"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":[0.0002432777,0.00005111911,0.0006233812,0.0003930422,0.00007751086,0.001089067,0.0003228536,0.11741,0.01373665,0.5729843,0.04728444,0.2457844],"study_design_scores_gemma":[0.0000268399,0.00005010554,0.0002249707,0.00007510393,0.00002177429,0.0006386644,0.00004783133,0.6408665,0.007154824,0.2339028,0.1169463,0.00004422258],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009432755,0.004802558,0.9315233,0.01012588,0.001793821,0.00004703621,0.0001289935,0.0006304329,0.04151523],"genre_scores_gemma":[0.6210244,0.01775843,0.2838618,0.006722643,0.002677721,0.0001869916,0.0003218587,0.0003074335,0.06713881],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001955471,"threshold_uncertainty_score":0.006541729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03089322038168945,"score_gpt":0.212730555322923,"score_spread":0.1818373349412336,"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."}}