{"id":"W2136225106","doi":"10.1109/ccece.1998.682759","title":"A pipelined systolic architecture for a Kalman-filter-based signal reconstruction algorithm","year":2002,"lang":"en","type":"article","venue":"","topic":"Analog and Mixed-Signal Circuit Design","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Pipeline (software); Computer science; Adder; Algorithm; Architecture; Kalman filter; Digital signal processing; Systolic array; Digital signal processor; SIGNAL (programming language); Throughput; Parallel computing; Signal processing; Data flow diagram; Reduction (mathematics); Real-time computing; Computer hardware; Embedded system; Very-large-scale integration; Artificial intelligence; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003500254,0.0002280348,0.0001433619,0.0002498056,0.0002499786,0.0003725551,0.0005699074,0.0003467683,0.004176001],"category_scores_gemma":[0.0004870686,0.0001680436,0.0002297296,0.000330745,0.0002508259,0.0004852138,0.0001883056,0.0003162071,0.000981021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003242423,"about_ca_system_score_gemma":0.0007354796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008238473,"about_ca_topic_score_gemma":0.001707432,"domain_scores_codex":[0.9998868,0.00002180135,0.000008766239,0.00002319879,0.00004667957,0.00001267054],"domain_scores_gemma":[0.9998436,0.00004956542,0.00001411433,0.00002481214,0.00005921346,0.000008731136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006171431,0.0001013327,0.001591292,0.000342848,0.00006481343,0.0002664211,0.0001972723,0.07628732,0.2779338,0.06072701,0.004547057,0.5773237],"study_design_scores_gemma":[0.000220164,0.001548464,0.002071091,0.00007482998,0.0001512106,0.0008264669,0.0000530408,0.8093197,0.1087689,0.02146263,0.0554422,0.00006124745],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02793637,0.0003014191,0.9668894,0.0001256804,0.00004990656,0.00003937255,0.00006720486,0.00117571,0.003414934],"genre_scores_gemma":[0.2844809,0.0003726688,0.7096134,0.00009852485,0.00005121585,0.00006916042,0.0002177532,0.000057615,0.005038767],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004176001,"threshold_uncertainty_score":0.01397008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01824712166509632,"score_gpt":0.1980951669577963,"score_spread":0.1798480452927,"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."}}