{"id":"W2119991158","doi":"10.1109/asic.1997.617014","title":"Pipelined adaptive filters","year":2002,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"STMicroelectronics (Canada)","funders":"","keywords":"Computer science; Adaptive filter; Equalization (audio); Channel (broadcasting); Adaptive equalizer; Point (geometry); Computer architecture; Algorithm; Telecommunications","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":[0.0006813162,0.0004556089,0.0003009874,0.0003590827,0.0004434285,0.0007200039,0.00105182,0.0005615638,0.005383621],"category_scores_gemma":[0.002154041,0.0003821308,0.0004240478,0.0003196903,0.0006021392,0.001143999,0.0004284083,0.0007802128,0.001036973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009073301,"about_ca_system_score_gemma":0.00106042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001635137,"about_ca_topic_score_gemma":0.002287684,"domain_scores_codex":[0.9993082,0.00007927924,0.00003421468,0.0001449986,0.000382259,0.00005103722],"domain_scores_gemma":[0.9992654,0.0002513976,0.0000817836,0.0001739838,0.0002071969,0.00002028296],"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":[0.000548444,0.00008896554,0.0009499908,0.0005014397,0.00009554172,0.0002283973,0.0002311985,0.131105,0.2383827,0.225341,0.004967379,0.39756],"study_design_scores_gemma":[0.0001441937,0.0003932804,0.0005311193,0.00008705664,0.00009063048,0.0003115986,0.00002908849,0.7098976,0.1623397,0.04250332,0.08361092,0.00006142737],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005280029,0.000228397,0.9893087,0.00006901081,0.00005832808,0.00005319318,0.00005279805,0.0008959941,0.004053452],"genre_scores_gemma":[0.2789636,0.0007948469,0.7104671,0.000178026,0.00006658554,0.0001812785,0.0001844615,0.0001551956,0.009008912],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005383621,"threshold_uncertainty_score":0.01800996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03294143694257283,"score_gpt":0.2340662978053021,"score_spread":0.2011248608627293,"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."}}