{"id":"W2898355885","doi":"10.1016/j.amc.2018.10.001","title":"An extended synchronization analysis for memristor-based coupled neural networks via aperiodically intermittent control","year":2018,"lang":"en","type":"article","venue":"Applied Mathematics and Computation","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; Natural Science Foundation of Guangxi Province; National Natural Science Foundation of China","keywords":"Memristor; Control theory (sociology); Synchronization (alternating current); Intermittent control; Artificial neural network; Computer science; Monotonic function; Control (management); Controller (irrigation); Mathematics; Control engineering; Artificial intelligence; Engineering; Channel (broadcasting)","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":[0.0003835995,0.0001930432,0.0003220644,0.0001327909,0.0003436093,0.0003780781,0.0002780467,0.00009505262,0.000007764605],"category_scores_gemma":[0.00001747667,0.000180991,0.00008169664,0.0005666085,0.0001164424,0.0002669668,0.00003775346,0.00007412754,0.000001716775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005338818,"about_ca_system_score_gemma":0.00003011133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005778114,"about_ca_topic_score_gemma":0.00002662345,"domain_scores_codex":[0.9985962,0.00003650231,0.0004437129,0.0004562575,0.0002224322,0.0002449183],"domain_scores_gemma":[0.9988075,0.0002172915,0.0002561937,0.0003330935,0.0002736957,0.0001122079],"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":[0.00008234508,0.000493916,0.0001257527,0.0001211725,0.0001903317,0.000001299199,0.001090504,0.7646597,0.0008307139,0.03877453,0.00003647151,0.1935933],"study_design_scores_gemma":[0.0007937964,0.0003127804,0.0009477442,0.000007267804,0.0001478686,0.000002079118,0.00003568763,0.9900476,0.000038631,0.007459616,0.000007047453,0.0001998241],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0253499,0.00002380462,0.973442,0.0001740698,0.0001428356,0.0006735715,0.000002127939,0.0001663621,0.00002535691],"genre_scores_gemma":[0.8603752,0.000001550204,0.1389538,0.0003785743,0.0001157144,0.00007487304,0.00008526909,0.00001370657,0.000001257793],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8350253,"threshold_uncertainty_score":0.7380598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01029068139985789,"score_gpt":0.2458323639347588,"score_spread":0.2355416825349009,"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."}}