{"id":"W2064590796","doi":"10.1155/2013/501461","title":"Lag Synchronization of Coupled Delayed Chaotic Neural Networks by Periodically Intermittent Control","year":2013,"lang":"en","type":"article","venue":"Abstract and Applied Analysis","topic":"Neural Networks Stability and Synchronization","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Lag; Control theory (sociology); Synchronization (alternating current); Intermittent control; Mathematics; Artificial neural network; Lyapunov stability; Chaotic; Stability (learning theory); Chaotic systems; Synchronization of chaos; Control (management); Time lag; Computer science; Topology (electrical circuits); Control engineering; Artificial intelligence; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001726604,0.0001685801,0.000378869,0.0001007363,0.0001419976,0.0002018794,0.0003093143,0.00009684059,0.0001287018],"category_scores_gemma":[0.00001094054,0.0001447909,0.000119271,0.0007313637,0.0001002676,0.000286258,0.00006810894,0.0001379457,0.00000569615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002323482,"about_ca_system_score_gemma":0.00001384096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001293644,"about_ca_topic_score_gemma":0.00003302438,"domain_scores_codex":[0.9986758,0.00003117488,0.0004557102,0.0003626415,0.0002219839,0.0002526936],"domain_scores_gemma":[0.9991025,0.0001237907,0.0002272149,0.0003177651,0.0001110938,0.0001176437],"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":[0.0000636447,0.0004917975,0.01740318,0.00007989127,0.001678323,0.000004825245,0.0008168704,0.7310488,0.008741573,0.004300619,0.0007251442,0.2346454],"study_design_scores_gemma":[0.0003561529,0.00004178994,0.02854464,0.00000345393,0.0001870297,0.000001032064,0.00002994273,0.9704761,0.00006129815,0.000147221,0.000007642819,0.0001436882],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4008274,0.0001451511,0.59838,0.0003070589,0.00003115674,0.0001911944,0.000002297295,0.00004328691,0.00007249184],"genre_scores_gemma":[0.9991767,0.00004171177,0.0003851927,0.0002522397,0.00003876002,0.00002540568,0.00005687655,0.000007228976,0.00001584063],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5983493,"threshold_uncertainty_score":0.59044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004113854578085109,"score_gpt":0.1919241976644701,"score_spread":0.187810343086385,"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."}}