{"id":"W3120110670","doi":"10.18280/ts.370607","title":"Design and Realization of a Hyperchaotic Memristive System for Communication System on FPGA","year":2020,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Memristor; Attractor; Field-programmable gate array; Chaotic; Lyapunov exponent; Nonlinear system; Computer science; Electronic circuit; Communications system; Secure communication; Realization (probability); CHAOS (operating system); Topology (electrical circuits); Electronic engineering; Control theory (sociology); Computer hardware; Mathematics; Engineering; Telecommunications; Physics; Encryption; Electrical engineering; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006421481,0.0002188357,0.0001660625,0.0001597822,0.0001926021,0.0002825551,0.0004682986,0.0002544995,0.002125614],"category_scores_gemma":[0.0000930852,0.00009051624,0.0001474862,0.0001006944,0.0001077469,0.0002322225,0.0001093695,0.0001751965,0.0002913006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001985542,"about_ca_system_score_gemma":0.0002142192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006380804,"about_ca_topic_score_gemma":0.0006203064,"domain_scores_codex":[0.9999481,0.000007105026,0.000004285056,0.00001070912,0.00001959044,0.00001019473],"domain_scores_gemma":[0.9999616,0.000006768842,0.000006199804,0.000006779211,0.00001447033,0.000004163333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004235945,0.0001048965,0.002279983,0.000746127,0.0001090235,0.001215827,0.0003603935,0.05430858,0.755697,0.02536788,0.002604865,0.1567818],"study_design_scores_gemma":[0.0002435479,0.001603915,0.004354395,0.0001000445,0.000120652,0.001831111,0.0001620894,0.5114881,0.4307739,0.005100239,0.04415962,0.00006242021],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3756351,0.001514594,0.5795148,0.0004426986,0.0003604009,0.0002963799,0.0002274288,0.002191234,0.03981745],"genre_scores_gemma":[0.9323107,0.0001965165,0.06345238,0.00004053441,0.00001518258,0.00007633049,0.00006744852,0.00001716968,0.003823769],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002125614,"threshold_uncertainty_score":0.007110894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04625716915970857,"score_gpt":0.2347973456922702,"score_spread":0.1885401765325617,"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."}}