{"id":"W2495860431","doi":"10.4018/978-1-60960-018-1.ch014","title":"A Novel DCGA Optimization Technique for Guaranteed BIBO-Stable Frequency-Response Masking Digital Filters Incorporating Bilinear Lossless Discrete-integrator IIR Interpolation Sub-Filters","year":2011,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Digital Filter Design and Implementation","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Bilinear interpolation; BIBO stability; Digital filter; Infinite impulse response; Bilinear transform; Mathematics; Algorithm; Interpolation (computer graphics); Transition band; Finite impulse response; Control theory (sociology); Frequency response; 2D Filters; Prototype filter; Filter design; Computer science; Filter (signal processing); Engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0005153521,0.0008510076,0.0006483257,0.0004814189,0.0002506925,0.001401013,0.001177986,0.000430644,0.0000112009],"category_scores_gemma":[0.000108903,0.0008481089,0.0004068231,0.0001735801,0.0001517322,0.001740065,0.0003928528,0.0003321584,0.00001958284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005727168,"about_ca_system_score_gemma":0.000497244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000076207,"about_ca_topic_score_gemma":0.00002995118,"domain_scores_codex":[0.9964015,0.00005832712,0.001173006,0.001158667,0.0005747628,0.0006337314],"domain_scores_gemma":[0.9973779,0.0001572253,0.001004863,0.0007948991,0.0004388553,0.0002262577],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001089167,0.00008395826,0.00007967567,0.0001764115,0.0002227599,0.00004309433,0.0005384907,0.0006426246,0.01247443,0.9747713,0.0004099699,0.009468135],"study_design_scores_gemma":[0.006945669,0.004466616,0.00005295672,0.004789216,0.0003587785,0.000656072,0.0004457562,0.3669312,0.03760922,0.5665632,0.003992391,0.007188926],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00008378624,0.00002890825,0.8946006,0.00004472853,0.0005862372,0.002123247,0.0008968473,0.0004129471,0.1012227],"genre_scores_gemma":[0.7929021,0.000003091541,0.2000946,0.0004905342,0.0003772513,0.0005391501,0.0004368616,0.000224028,0.004932406],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7928183,"threshold_uncertainty_score":0.9996356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03023351459799899,"score_gpt":0.2573575882210623,"score_spread":0.2271240736230632,"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."}}