{"id":"W1523547124","doi":"10.1109/iscas.2015.7169285","title":"Minimum jitter adaptive decision feedback equalizer for 4PAM serial links","year":2015,"lang":"en","type":"article","venue":"","topic":"Advancements in PLL and VCO Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Jitter; Adaptive equalizer; Computer science; Equalizer; CMOS; Cadence; Serial communication; IBM; Least mean squares filter; Electronic engineering; Channel (broadcasting); Intersymbol interference; Noise (video); Computer hardware; Adaptive filter; Algorithm; Engineering; Telecommunications; 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":[0.0003020421,0.0003102991,0.0002070317,0.0003209995,0.0003057058,0.0004066989,0.0004649694,0.0004577946,0.002136466],"category_scores_gemma":[0.0006981146,0.0001473451,0.0001656111,0.0002048474,0.0001471688,0.0004802844,0.0002440501,0.0004495166,0.0002983052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003063024,"about_ca_system_score_gemma":0.0002695686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006664752,"about_ca_topic_score_gemma":0.001630899,"domain_scores_codex":[0.9997939,0.0000376042,0.00001313309,0.00003928399,0.00009503114,0.00002111625],"domain_scores_gemma":[0.9998217,0.00007371083,0.00003009706,0.00001531032,0.00005269322,0.00000647264],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000990551,0.0001321093,0.002214759,0.0002327104,0.00008467848,0.0003987202,0.0001869306,0.06525239,0.4927548,0.01232955,0.00275576,0.4226669],"study_design_scores_gemma":[0.000120627,0.0007050172,0.002225987,0.00005706423,0.00009781779,0.0005505067,0.00005553958,0.6835091,0.2906107,0.002430203,0.01958392,0.00005359247],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1271155,0.0009510019,0.8656641,0.0002982241,0.0001961437,0.00005715968,0.00008794991,0.00104035,0.004589641],"genre_scores_gemma":[0.8412083,0.0004041362,0.1504224,0.000165802,0.00009666414,0.00005734517,0.0001019313,0.00004206528,0.00750138],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002136466,"threshold_uncertainty_score":0.007147193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05608660645972777,"score_gpt":0.291536254193275,"score_spread":0.2354496477335472,"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."}}