{"id":"W1957158527","doi":"10.1109/iscas.1993.393796","title":"A method of evaluating the effects of signal quantization at arbitrary locations in recursive digital filters","year":2002,"lang":"en","type":"article","venue":"1993 IEEE International Symposium on Circuits and Systems","topic":"Digital Filter Design and Implementation","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Quantization (signal processing); Upper and lower bounds; Digital filter; Algorithm; Computer science; Iterative method; Norm (philosophy); Digital signal processing; Invariant (physics); Recursive filter; Mathematics; Filter (signal processing); Mathematical analysis; Root-raised-cosine filter; 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":[0.00155911,0.0008725055,0.0006294867,0.0007619677,0.000457191,0.0011333,0.001090352,0.0009822864,0.002198626],"category_scores_gemma":[0.01313367,0.0004431927,0.0004681852,0.0007463917,0.001009234,0.001516146,0.0008016103,0.001180344,0.0006399207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008182025,"about_ca_system_score_gemma":0.0009232752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002025554,"about_ca_topic_score_gemma":0.002574682,"domain_scores_codex":[0.9982482,0.0004277295,0.0000737496,0.0001681783,0.001010727,0.00007147899],"domain_scores_gemma":[0.9931859,0.004403049,0.0005559142,0.0007673731,0.001013148,0.0000746447],"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":[0.0003463071,0.00008994906,0.001160833,0.0002736045,0.00008933584,0.0001170678,0.0002266207,0.5233516,0.09795693,0.07702648,0.001077966,0.2982834],"study_design_scores_gemma":[0.00001141076,0.00009952612,0.0003036349,0.00001617573,0.00001489343,0.00008818887,0.00001435969,0.9413137,0.0468259,0.009718019,0.001571378,0.00002278994],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003049925,0.00005116441,0.9960418,0.00001025325,0.000007366204,0.00001545485,0.00001087079,0.0002708769,0.0005422469],"genre_scores_gemma":[0.1207584,0.0001629234,0.8773075,0.00002665169,0.00001229354,0.0001009073,0.00006432439,0.000171279,0.001395733],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002198626,"threshold_uncertainty_score":0.008245468,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05742613038314944,"score_gpt":0.3197901600267265,"score_spread":0.2623640296435771,"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."}}