{"id":"W2913363600","doi":"10.1016/j.apm.2019.01.041","title":"A new method for quantized sampled-data synchronization of delayed chaotic Lur’e systems","year":2019,"lang":"en","type":"article","venue":"Applied Mathematical Modelling","topic":"Neural Networks Stability and Synchronization","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Synchronization (alternating current); Control theory (sociology); Mathematics; Sampling (signal processing); Chaotic; Controller (irrigation); Zero (linguistics); Chaotic systems; Control (management); Computer science; Artificial intelligence; Topology (electrical circuits)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009368531,0.0001855144,0.0004938005,0.00006894587,0.0000707801,0.0001011714,0.0009972972,0.000120556,0.00002368195],"category_scores_gemma":[0.00005435544,0.0001654289,0.00006411538,0.0003643211,0.00001753162,0.0003105893,0.0002598182,0.0001026604,0.00003747701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004024746,"about_ca_system_score_gemma":0.0001016017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002598669,"about_ca_topic_score_gemma":0.000001513753,"domain_scores_codex":[0.9980474,0.00004507304,0.000660843,0.0005941553,0.0003369718,0.0003155599],"domain_scores_gemma":[0.9971619,0.001134192,0.0002426373,0.001249196,0.0001119864,0.0001000852],"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":[0.00001819413,0.00003560408,9.244807e-7,0.0003687745,0.00002026856,9.003681e-8,0.0001928464,0.422291,0.0003628515,0.5738118,0.0000477256,0.002849844],"study_design_scores_gemma":[0.0004678507,0.00004384773,1.525179e-7,0.00006926746,0.00002897427,0.000002943779,0.00002216077,0.809828,0.000247358,0.1890947,0.00005082115,0.0001439564],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000824534,0.00009702484,0.9968569,0.0001023164,0.0001674489,0.001503302,0.000008839475,0.0001325675,0.000307034],"genre_scores_gemma":[0.4015247,0.000006613826,0.5982817,0.00002427171,0.00005149766,0.00002352267,0.0000344865,0.00001709264,0.00003612932],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4007002,"threshold_uncertainty_score":0.6745993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05837770335222597,"score_gpt":0.2997416671606069,"score_spread":0.2413639638083809,"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."}}