{"id":"W2468745936","doi":"10.1007/s10470-016-0791-4","title":"Hardware implementation of subsampled adaptive subband digital predistortion algorithm","year":2016,"lang":"en","type":"article","venue":"Analog Integrated Circuits and Signal Processing","topic":"Advanced Power Amplifier Design","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure","funders":"Centre National de la Recherche Scientifique; Agence Nationale de la Recherche","keywords":"Predistortion; Amplifier; Computer science; Electronic engineering; Bandwidth (computing); Energy consumption; Efficient energy use; Adjacent channel power ratio; Electrical engineering; Engineering; Telecommunications","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":[0.0001270504,0.000398855,0.0002903759,0.0004292518,0.0003289325,0.0005457727,0.0006866417,0.0003353134,0.00660434],"category_scores_gemma":[0.0003912587,0.0001686206,0.0001849497,0.0002615856,0.0001067363,0.00032849,0.0002435104,0.0003184756,0.00166445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002509462,"about_ca_system_score_gemma":0.0005632999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001459109,"about_ca_topic_score_gemma":0.00247453,"domain_scores_codex":[0.9998409,0.00002228343,0.00001197709,0.00003575409,0.00006612219,0.00002295439],"domain_scores_gemma":[0.9998575,0.00003027662,0.00001268572,0.00002750846,0.00006430875,0.000007625656],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005618145,0.0001014857,0.001364316,0.0002659645,0.00009436969,0.0003259747,0.0002347518,0.01930682,0.2774323,0.009763944,0.006999221,0.683549],"study_design_scores_gemma":[0.0001790021,0.0008541416,0.005230505,0.00005426203,0.00015293,0.001599978,0.0001136029,0.5731203,0.3672698,0.002868408,0.04848057,0.00007650568],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06412808,0.00064659,0.9186266,0.0002429814,0.0002273317,0.0001376604,0.0001940715,0.005357499,0.01043918],"genre_scores_gemma":[0.5416802,0.0003849417,0.4460426,0.0002913203,0.00009952423,0.0001503094,0.0004601129,0.00007508966,0.01081607],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00660434,"threshold_uncertainty_score":0.02209371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01353131631269295,"score_gpt":0.2328363327170277,"score_spread":0.2193050164043347,"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."}}