{"id":"W4403126750","doi":"10.1109/iwaenc61483.2024.10694445","title":"A Third-Order Tensor Decomposition Based Linear-In-The-Parameters Nonlinear Adaptive Filter","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Adaptive Filtering Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"","keywords":"Nonlinear system; Tensor (intrinsic definition); Tensor decomposition; Filter (signal processing); Adaptive filter; Order (exchange); Computer science; Mathematics; Algorithm; Physics; Computer vision; Geometry","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":[0.000715649,0.0007718366,0.0004963552,0.0003466822,0.0004082955,0.0005413156,0.0007802556,0.0007179306,0.001693749],"category_scores_gemma":[0.001336102,0.0002621383,0.0006510569,0.0004655334,0.0005044208,0.0009579869,0.0006148547,0.0009578655,0.0007651038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005226058,"about_ca_system_score_gemma":0.001019017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006468284,"about_ca_topic_score_gemma":0.006908021,"domain_scores_codex":[0.9996911,0.00007450208,0.00001854912,0.00007437082,0.000107704,0.00003374435],"domain_scores_gemma":[0.9996275,0.0000852509,0.00004289862,0.00004346456,0.0001737278,0.00002711815],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002666995,0.0001135637,0.001681491,0.0002002846,0.0001180286,0.0001526497,0.0002146967,0.461266,0.07737978,0.02902668,0.004636634,0.4249435],"study_design_scores_gemma":[0.000004500664,0.00004184146,0.0001287238,0.000006109904,0.00001075251,0.00003678444,0.000006537389,0.9924124,0.004455713,0.001261007,0.001623323,0.00001221004],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003996603,0.00009230952,0.9948882,0.00005632961,0.00003373853,0.00001397476,0.00002644735,0.0001890955,0.0007031763],"genre_scores_gemma":[0.308305,0.0006113531,0.6822705,0.0001843135,0.00008171401,0.0001778259,0.0004534304,0.000124721,0.007791182],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006468284,"threshold_uncertainty_score":0.01286131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02187622604513283,"score_gpt":0.278034101837131,"score_spread":0.2561578757919982,"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."}}