{"id":"W2066159339","doi":"10.4304/jcp.7.6.1289-1296","title":"A Novel Discrete Particle Swarm Optimization for FRM FIR Digital Filters","year":2012,"lang":"en","type":"article","venue":"Journal of Computers","topic":"Digital Filter Design and Implementation","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Particle swarm optimization; Finite impulse response; Digital filter; Computer science; Mathematics; Algorithm; Filter (signal processing); Computer vision","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":[0.0005478081,0.0006069862,0.0006653316,0.0003193862,0.0003004427,0.0005328676,0.0007142114,0.001216122,0.001485023],"category_scores_gemma":[0.001076563,0.0002929399,0.0005288686,0.0002992983,0.0004152249,0.0003835853,0.0004744921,0.0005732526,0.0003335235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003882563,"about_ca_system_score_gemma":0.000626002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002451745,"about_ca_topic_score_gemma":0.002020603,"domain_scores_codex":[0.9997482,0.00007191155,0.00001468689,0.00004765527,0.00009640557,0.00002123291],"domain_scores_gemma":[0.9997731,0.000102237,0.00002969103,0.00001715554,0.0000624962,0.00001538835],"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":[0.00008687368,0.00006365623,0.00059201,0.0001370408,0.00005957778,0.0001008133,0.00008343389,0.8966044,0.007748907,0.01043577,0.001460206,0.08262726],"study_design_scores_gemma":[0.00001231742,0.00003052061,0.0000579706,0.000003542045,0.000003841184,0.00001050378,0.000002705721,0.9985408,0.0003245958,0.0004061407,0.000604275,0.000002818871],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007282958,0.000172645,0.989997,0.0001046251,0.00007168535,0.00003680251,0.00001677334,0.0001331337,0.002184468],"genre_scores_gemma":[0.3495486,0.0003091138,0.6436229,0.0001773561,0.0001081169,0.000316621,0.0001100259,0.00004950273,0.005757671],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002451745,"threshold_uncertainty_score":0.004967868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03555435339319439,"score_gpt":0.2801804294262905,"score_spread":0.2446260760330961,"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."}}