{"id":"W2094325660","doi":"10.1109/ccece.2013.6567785","title":"FPGA implementation of floating-point complex matrix inversion based on GAUSS-JORDAN elimination","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton; Université du Québec à Trois-Rivières","funders":"","keywords":"Floating point; Field-programmable gate array; Gaussian elimination; Computer science; Inversion (geology); Gauss; Matrix (chemical analysis); Algorithm; Parallel computing; Computer hardware","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009292963,0.0001079046,0.0001150282,0.0001650992,0.00004195167,0.00001378524,0.0001601786,0.00004090182,0.001060505],"category_scores_gemma":[0.00001345726,0.0001096476,0.00003539136,0.0001592695,0.00002124895,0.0002349705,0.00003175148,0.00008028965,0.00005113184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001067715,"about_ca_system_score_gemma":0.00000759664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001727282,"about_ca_topic_score_gemma":0.00002585969,"domain_scores_codex":[0.9992978,0.00003253721,0.000293943,0.00009568554,0.0001612626,0.0001187522],"domain_scores_gemma":[0.9993519,0.00007889815,0.00007875398,0.000352723,0.0001032232,0.00003446111],"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":[0.00001575319,0.0001305048,0.0009287812,0.0003167616,0.00002947434,4.146576e-7,0.0006344852,0.1020816,0.5229431,0.01500778,0.0250213,0.33289],"study_design_scores_gemma":[0.0003024687,0.00007869079,0.005832536,0.00002721452,0.000004036649,1.904944e-7,0.0004956911,0.4089659,0.5828766,0.000853341,0.0004344505,0.0001289103],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2569875,0.00002198619,0.7269699,0.001076412,0.00007472975,0.001126268,0.00001479697,0.001426158,0.01230231],"genre_scores_gemma":[0.9136904,0.00002138685,0.08600741,0.00009202988,0.000008334251,0.00004309291,0.00008895674,0.00002220844,0.00002619381],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6567029,"threshold_uncertainty_score":0.9998527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01646912992386517,"score_gpt":0.2947729621108419,"score_spread":0.2783038321869767,"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."}}