{"id":"W1972734271","doi":"10.1109/ccece.2014.6901147","title":"Wavelet based OFDM for Power line Communication","year":2014,"lang":"en","type":"article","venue":"","topic":"Power Line Communications and Noise","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Cyclic prefix; Orthogonal frequency-division multiplexing; Power-line communication; Computer science; Wavelet; Wavelet transform; Fast Fourier transform; Electronic engineering; Communications system; Interference (communication); Wavelet packet decomposition; Finite impulse response; Filter bank; Channel (broadcasting); Algorithm; Power (physics); Telecommunications; Engineering; Artificial intelligence","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":[0.0001257872,0.0001804396,0.0001737097,0.0002100268,0.0001241842,0.0003393479,0.0001975702,0.0003732818,0.00246835],"category_scores_gemma":[0.0003588615,0.00007817213,0.0001323969,0.0005285693,0.0001685119,0.0003769631,0.0001658484,0.0004986245,0.0007827299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001641482,"about_ca_system_score_gemma":0.0001329339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002916702,"about_ca_topic_score_gemma":0.0002546303,"domain_scores_codex":[0.9999143,0.0000180216,0.000003584838,0.00001247139,0.00004520189,0.000006481924],"domain_scores_gemma":[0.9999086,0.00003857498,0.00001114064,0.00001247205,0.00002487765,0.000004380735],"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":[0.0002384392,0.00009943658,0.0009010176,0.0004730946,0.00004324115,0.0007948978,0.000142192,0.06879221,0.1358694,0.1427775,0.01210006,0.6377686],"study_design_scores_gemma":[0.00004827376,0.0004618926,0.002215263,0.0001485142,0.00004402255,0.001222247,0.00008960393,0.7845401,0.04370512,0.05694476,0.1105301,0.000050112],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03067058,0.009478599,0.9427264,0.0007407009,0.0003852918,0.00003896411,0.0001371973,0.000351157,0.01547106],"genre_scores_gemma":[0.5087942,0.02207878,0.436217,0.0003277988,0.0006059688,0.0001177002,0.00046043,0.0001173116,0.03128081],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00246835,"threshold_uncertainty_score":0.008257449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01190019819414683,"score_gpt":0.2301526330750722,"score_spread":0.2182524348809254,"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."}}