{"id":"W4367321651","doi":"10.3390/electronics12092010","title":"Digital Finite Impulse Response Equalizer for Nonlinear Frequency Response Compensation in Wireless Communication","year":2023,"lang":"en","type":"article","venue":"Electronics","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Predistortion; Frequency response; Finite impulse response; Electronic engineering; Nonlinear distortion; Impulse response; Phase distortion; Nonlinear system; Phase response; Computer science; Amplifier; Control theory (sociology); Frequency band; Filter (signal processing); Engineering; Electrical engineering; Telecommunications; Bandwidth (computing); Mathematics; Physics","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":[0.0003583292,0.0003687624,0.0002034223,0.0002995615,0.0002037581,0.0003905666,0.000377829,0.0004433721,0.004794006],"category_scores_gemma":[0.0006955661,0.0001179299,0.0001948616,0.0002655549,0.0002219395,0.0004577889,0.0001807935,0.0004635798,0.0011733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003316047,"about_ca_system_score_gemma":0.0002602331,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004913663,"about_ca_topic_score_gemma":0.0009760676,"domain_scores_codex":[0.9997991,0.00005626664,0.000009592948,0.00003395946,0.00008682982,0.00001431251],"domain_scores_gemma":[0.9998084,0.00009410654,0.00001816117,0.00002437145,0.00004994535,0.000005146735],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004060895,0.0001256838,0.0009528435,0.0004461005,0.00007936869,0.0003567699,0.0001804308,0.03968978,0.4795654,0.02438435,0.002960089,0.4508532],"study_design_scores_gemma":[0.00006503175,0.0007697021,0.00192817,0.0001081208,0.0001021384,0.00149222,0.00005070816,0.3525098,0.5784067,0.004489811,0.06002149,0.00005614289],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02194456,0.0007946537,0.9680265,0.0001151328,0.00008906503,0.00006929225,0.00004393517,0.001287446,0.007629388],"genre_scores_gemma":[0.50278,0.0009764854,0.4790314,0.0001528023,0.00006206335,0.0001072387,0.0001617562,0.0001327936,0.01659545],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004794006,"threshold_uncertainty_score":0.01603752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02384044002161021,"score_gpt":0.3088942998299459,"score_spread":0.2850538598083357,"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."}}