{"id":"W2112962626","doi":"10.1109/icassp.2012.6288670","title":"Minimax design of sparse FIR digital filters","year":2012,"lang":"en","type":"article","venue":"","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Minimax; Mathematical optimization; Finite impulse response; Iterative method; Computer science; Convergence (economics); Dual (grammatical number); Optimal design; Filter (signal processing); Point (geometry); Iterative design; Digital filter; Algorithm; 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":[0.0009166861,0.000527866,0.0007241174,0.0003227382,0.0002470856,0.0005659382,0.000544198,0.000842048,0.001466664],"category_scores_gemma":[0.001974706,0.0004463183,0.0004171458,0.0002690176,0.0005602054,0.0007112141,0.0005833983,0.0007260696,0.0003340142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003915915,"about_ca_system_score_gemma":0.0005652162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003463368,"about_ca_topic_score_gemma":0.0005053458,"domain_scores_codex":[0.9996345,0.0001006932,0.00001830288,0.00006699231,0.0001556906,0.000023665],"domain_scores_gemma":[0.9995255,0.0002677574,0.00006521053,0.00003539952,0.00009133291,0.00001478235],"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":[0.0001439536,0.00006422061,0.0003864841,0.0002081353,0.00004715452,0.00008539575,0.0001457624,0.7605448,0.04071362,0.04112677,0.001151908,0.1553818],"study_design_scores_gemma":[0.00001810703,0.00005846353,0.0000571515,0.000008688569,0.000005135842,0.00003009284,0.00000614088,0.9901679,0.00418807,0.004202894,0.001251993,0.000005361844],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004007208,0.00004917951,0.9952648,0.00003288344,0.000009120523,0.00001194435,0.000006067685,0.0000402745,0.0005785212],"genre_scores_gemma":[0.2537257,0.0002692421,0.7418309,0.0001059212,0.00005030605,0.0002137515,0.00006582832,0.000059627,0.003678728],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001466664,"threshold_uncertainty_score":0.004906476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05893694443655142,"score_gpt":0.2802597986621528,"score_spread":0.2213228542256014,"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."}}