{"id":"W2770061147","doi":"10.1007/978-0-387-74759-0_610","title":"Signal Processing with Higher Order Statistics","year":2008,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Optimization","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Higher-order statistics; Statistics; Signal processing; SIGNAL (programming language); Computer science; Order statistic; Order (exchange); Mathematics; Digital signal processing; Computer hardware; Economics; Programming language","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":[0.0004532897,0.001321931,0.001282484,0.0009967397,0.0002462662,0.0019745,0.0007085831,0.0009195931,0.01859204],"category_scores_gemma":[0.001227895,0.0004451017,0.0005631096,0.002247032,0.0009601059,0.00142017,0.0008365278,0.002402928,0.0155442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003196757,"about_ca_system_score_gemma":0.0005763606,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003715202,"about_ca_topic_score_gemma":0.0005908628,"domain_scores_codex":[0.9995602,0.00007570229,0.00002745167,0.00006981161,0.0002467086,0.00002027629],"domain_scores_gemma":[0.9995376,0.0002283759,0.00002050541,0.00009862817,0.0001015769,0.00001343858],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005647241,0.0000477775,0.0001063243,0.0008177658,0.0000696179,0.0001481169,0.000148408,0.01553551,0.01244166,0.3209969,0.0818919,0.5677395],"study_design_scores_gemma":[0.00002882046,0.0001155155,0.0006812389,0.000282922,0.00005754818,0.000914695,0.0000416218,0.1146942,0.01209806,0.4212981,0.449701,0.00008629593],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001083525,0.01519421,0.9043341,0.000494137,0.001438422,0.00003002764,0.0002039834,0.001283323,0.07593828],"genre_scores_gemma":[0.0430376,0.04390636,0.6493372,0.0008115398,0.003678765,0.0002338827,0.001175859,0.001601889,0.2562168],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01859204,"threshold_uncertainty_score":0.06219655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01257321603035024,"score_gpt":0.2279365445735584,"score_spread":0.2153633285432081,"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."}}