{"id":"W2128392196","doi":"10.1109/icc.1991.162467","title":"Performance of reduced computation trellis decoders for mobile radio with frequency selective fading","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Fading; Viterbi algorithm; Trellis (graph); Phase-shift keying; Algorithm; Computer science; Decoding methods; Viterbi decoder; Keying; Computation; Trellis modulation; Convolutional code; Electronic engineering; Bit error rate; Telecommunications; Engineering","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":[0.0008631739,0.0004753656,0.0005901508,0.000693091,0.0004525105,0.0009938631,0.0007618201,0.0006694618,0.004617933],"category_scores_gemma":[0.004438316,0.0001773297,0.0003918649,0.0006921765,0.0003966648,0.0007413116,0.0003736711,0.0004529937,0.0009730667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001302042,"about_ca_system_score_gemma":0.001450244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007295612,"about_ca_topic_score_gemma":0.008383271,"domain_scores_codex":[0.9993017,0.0002376937,0.00004134513,0.00008115506,0.0002469376,0.00009114436],"domain_scores_gemma":[0.9973875,0.001557187,0.0002464873,0.0002461387,0.0005122218,0.00005049232],"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":[0.002066471,0.00009513883,0.001730653,0.0002195847,0.0001599812,0.0002053003,0.0001794052,0.7352981,0.04060963,0.02038369,0.003622309,0.1954297],"study_design_scores_gemma":[0.00006674645,0.0002492824,0.0003805531,0.00001487503,0.00002790607,0.0001492566,0.00002254147,0.9719484,0.02402758,0.00173693,0.001352024,0.00002381012],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3029274,0.001628187,0.6778804,0.000435361,0.0001109996,0.0001284483,0.0004380259,0.0040752,0.01237599],"genre_scores_gemma":[0.7841195,0.0007169937,0.2063392,0.0001163544,0.00006477044,0.0001085372,0.0006777233,0.0001962086,0.007660809],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007295612,"threshold_uncertainty_score":0.01544851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01442925356270055,"score_gpt":0.238023508626194,"score_spread":0.2235942550634935,"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."}}