{"id":"W2902860349","doi":"10.1155/2018/8456737","title":"Finite‐Time Synchronization for Complex‐Valued Recurrent Neural Networks with Time Delays","year":2018,"lang":"en","type":"article","venue":"Complexity","topic":"Neural Networks Stability and Synchronization","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Settling time; Synchronization (alternating current); Computer science; Control theory (sociology); Artificial neural network; Controller (irrigation); Nonlinear system; Lyapunov function; Function (biology); Control (management); Artificial intelligence; Control engineering; Step response","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003777524,0.0002883107,0.0003390366,0.00007482555,0.00066572,0.0002550226,0.0008479688,0.0001006941,0.000275272],"category_scores_gemma":[0.0000878486,0.0002541277,0.00009093768,0.0007307172,0.000431445,0.0005621286,0.0002671044,0.000163614,0.0001181953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001331031,"about_ca_system_score_gemma":0.00006732716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001113109,"about_ca_topic_score_gemma":0.00005149802,"domain_scores_codex":[0.9978114,0.0002135058,0.000394354,0.0007019722,0.000306238,0.0005725342],"domain_scores_gemma":[0.9980484,0.0002827577,0.0002058549,0.0007745522,0.000525258,0.0001631648],"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":[0.001546501,0.001864828,0.004888217,0.0003728758,0.0003476454,0.00002924723,0.003101701,0.4435706,0.000943252,0.1153913,0.07599504,0.3519488],"study_design_scores_gemma":[0.0006685205,0.0008199873,0.001591487,0.00002790647,0.00001370012,0.00001481788,0.000003145938,0.9918633,0.00004567421,0.003244312,0.001376035,0.0003310762],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007874038,0.00004621549,0.9891696,0.0007799098,0.000383469,0.0008102248,0.00002177858,0.0004052886,0.0005094804],"genre_scores_gemma":[0.9261624,0.000002550843,0.07200649,0.0006123402,0.000714767,0.00004343913,0.0003011517,0.00003060821,0.0001262816],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9182884,"threshold_uncertainty_score":0.9999911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04703993632721799,"score_gpt":0.2646748018557175,"score_spread":0.2176348655284995,"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."}}