{"id":"W2013930007","doi":"10.1109/icecs.2011.6122304","title":"FPGA-implementation of high-speed MLP neural network","year":2011,"lang":"en","type":"article","venue":"","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Rimouski","funders":"","keywords":"Computer science; Field-programmable gate array; Backpropagation; Artificial neural network; Multilayer perceptron; Parallel computing; Activation function; Critical path method; Path (computing); Nonlinear system; Perceptron; Embedded system; 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":[0.00006817086,0.00006115236,0.00007973907,0.00001866806,0.00005665349,0.00001980998,0.0003886604,0.000017114,0.0002196224],"category_scores_gemma":[6.429061e-7,0.00005057792,0.00003182858,0.0002820809,0.0000184873,0.0002050925,0.0001116993,0.00003883409,0.00002375686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004538292,"about_ca_system_score_gemma":0.000009753452,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000408447,"about_ca_topic_score_gemma":0.00007602023,"domain_scores_codex":[0.9993826,0.00001805854,0.0001766846,0.0001632718,0.00009635546,0.000163009],"domain_scores_gemma":[0.9995227,0.00002137507,0.00007635525,0.0002983081,0.00003754983,0.00004371834],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000003657014,0.00005287855,0.00265584,0.000003981354,0.0000140447,0.000001895677,0.0003349656,0.00114309,0.0005472827,0.7982553,0.01623415,0.1807529],"study_design_scores_gemma":[0.001944964,0.0007275904,0.5237441,0.00002343404,0.00004957574,0.00003046938,0.0002893388,0.1564199,0.1122003,0.192666,0.01088611,0.001018238],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.387438,0.00005171004,0.5983866,0.001511418,0.000549709,0.0004272863,0.000002672217,0.0002769686,0.01135564],"genre_scores_gemma":[0.9663582,0.000005235696,0.03303255,0.0003488997,0.00007973339,0.000006962555,0.000002489946,0.000003546951,0.0001623507],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6055893,"threshold_uncertainty_score":0.2404711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03860625694814743,"score_gpt":0.2740014172305932,"score_spread":0.2353951602824458,"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."}}