{"id":"W1551448255","doi":"10.1109/iscas.1995.520383","title":"Design of 2-D FIR filters by feedback neural networks","year":2002,"lang":"en","type":"article","venue":"","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Finite impulse response; Very-large-scale integration; Artificial neural network; Computer science; Filter (signal processing); Network synthesis filters; Hopfield network; Electronic engineering; Control theory (sociology); Algorithm; Artificial intelligence; Engineering; Embedded system","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.00005001533,0.00008002522,0.00009193458,0.00001647336,0.00005812667,0.00004666586,0.0005555726,0.00003151611,0.0001459456],"category_scores_gemma":[0.000001989239,0.00006556612,0.00003559608,0.0002915584,0.00003173232,0.0001720503,0.00008644578,0.00007084508,0.00002628416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005160413,"about_ca_system_score_gemma":0.000001617378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008272265,"about_ca_topic_score_gemma":4.707195e-7,"domain_scores_codex":[0.999336,0.00002774408,0.0001509284,0.0001975498,0.00009775064,0.0001900319],"domain_scores_gemma":[0.9994159,0.00009574842,0.00005245686,0.0003505663,0.00002236434,0.00006299117],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00000185575,0.00009593175,0.00007260685,0.000002769642,0.000009355921,0.00000184832,0.00005375549,0.1717209,0.001666324,0.006446869,0.7247855,0.09514232],"study_design_scores_gemma":[0.00009185674,0.00003764982,0.00005577245,0.000002136273,0.000001530809,0.000003335338,0.000001642245,0.9968166,0.0005116509,0.0001752254,0.002223522,0.00007906722],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0009365114,0.0002229303,0.9952135,0.001892837,0.00008512737,0.0001269067,6.409355e-7,0.00008969873,0.001431809],"genre_scores_gemma":[0.9714944,0.00006512717,0.02535431,0.001026619,0.00004382233,0.00001564488,0.000001297907,0.000005968152,0.001992835],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9705579,"threshold_uncertainty_score":0.2673709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02739509753567642,"score_gpt":0.2153041696195373,"score_spread":0.1879090720838609,"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."}}