{"id":"W1831550379","doi":"10.1109/pacrim.2001.953688","title":"Frequency domain equalization for high data rate multipath channels","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Adaptive Filtering Techniques","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Algorithm; Multipath propagation; Frequency domain; Bit error rate; Fast Fourier transform; Phase-shift keying; Electronic engineering; Delay spread; Time domain; Adaptive equalizer; Equalization (audio); Channel (broadcasting); Telecommunications; Decoding methods; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002351403,0.0002511492,0.0002213292,0.0002871833,0.0001748417,0.0003239101,0.0001864237,0.0003198296,0.002776995],"category_scores_gemma":[0.001229828,0.00008925915,0.0001246776,0.0002903235,0.0002451691,0.0005272301,0.0001689281,0.0002814571,0.0009577236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002030092,"about_ca_system_score_gemma":0.0002846647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003953791,"about_ca_topic_score_gemma":0.00108182,"domain_scores_codex":[0.9998838,0.00002529746,0.000004040871,0.00001166158,0.00006347863,0.00001167328],"domain_scores_gemma":[0.9996516,0.0002003251,0.00002966738,0.00004771542,0.00006583824,0.000004917309],"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":[0.0003030817,0.00007328673,0.001447716,0.0002034626,0.00003453563,0.0001962841,0.00009317046,0.08634468,0.3878083,0.02659207,0.001610412,0.4952931],"study_design_scores_gemma":[0.00004104446,0.0003069491,0.004011157,0.00003251269,0.00003039407,0.000878754,0.00006050605,0.6691741,0.2905161,0.01680218,0.01810653,0.00003986472],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05194725,0.0004337792,0.9435845,0.000148379,0.00004635632,0.00002656326,0.00003059717,0.000514592,0.003267995],"genre_scores_gemma":[0.3933511,0.001321845,0.5975463,0.00006856934,0.00006871997,0.00004914821,0.0001056788,0.00008376355,0.007404769],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002776995,"threshold_uncertainty_score":0.00928992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08149203225250119,"score_gpt":0.2770503414852442,"score_spread":0.195558309232743,"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."}}