{"id":"W2090005916","doi":"10.1109/icassp.2002.5745188","title":"Schroeder sequences for time dispersive frequency selective channel estimation using DFT and Least Sum of Squared Errors methods","year":2002,"lang":"en","type":"article","venue":"IEEE International Conference on Acoustics Speech and Signal Processing","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Intersymbol interference; Algorithm; Channel (broadcasting); Computer science; Sequence (biology); Mean squared error; Detector; Discrete Fourier transform (general); Block (permutation group theory); Interference (communication); Telecommunications; Mathematics; Statistics; Fourier transform; Fourier analysis; Short-time Fourier transform","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":[0.001099892,0.0006703611,0.0003697546,0.0006227158,0.0001628392,0.000410422,0.0004604472,0.0006745704,0.00194823],"category_scores_gemma":[0.004366456,0.0002142343,0.0002451455,0.0005756639,0.0003996266,0.0009650389,0.000397126,0.0006026806,0.0008887639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002937305,"about_ca_system_score_gemma":0.0005419431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009918691,"about_ca_topic_score_gemma":0.001581728,"domain_scores_codex":[0.9992798,0.0003447096,0.00003869437,0.00005511204,0.0002560492,0.0000257293],"domain_scores_gemma":[0.9985623,0.0009122483,0.0001310274,0.0001600833,0.0002109012,0.00002342091],"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":[0.000428182,0.0001204903,0.001003722,0.0001942316,0.00005811221,0.0001728255,0.0002256481,0.4252023,0.04181464,0.1436265,0.001689581,0.3854637],"study_design_scores_gemma":[0.00002217291,0.00009909954,0.0002290912,0.00002092942,0.000009928774,0.00009634579,0.00001846566,0.964875,0.01588895,0.01581306,0.002904415,0.00002247619],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004700286,0.0001604194,0.994381,0.00004234752,0.00001872657,0.00001767202,0.00001491731,0.0001097143,0.0005549602],"genre_scores_gemma":[0.1123665,0.0004105745,0.8842075,0.00006174893,0.00004089225,0.0001050914,0.0001429972,0.00005743603,0.002607314],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00194823,"threshold_uncertainty_score":0.006517529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06494685467948837,"score_gpt":0.3477170532596043,"score_spread":0.2827701985801159,"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."}}