{"id":"W2049871086","doi":"10.1016/j.sysconle.2004.06.008","title":"Iterative least-squares solutions of coupled Sylvester matrix equations","year":2004,"lang":"en","type":"article","venue":"Systems & Control Letters","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":417,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Sylvester matrix; Sylvester equation; Iterative method; Mathematics; Sylvester's law of inertia; Matrix-free methods; Least-squares function approximation; Applied mathematics; Matrix (chemical analysis); Block (permutation group theory); Gauss–Seidel method; Augmented matrix; Mathematical optimization; Algorithm; State-transition matrix; Sparse matrix; Symmetric matrix; Mathematical analysis; Eigenvalues and eigenvectors; Polynomial matrix; Polynomial","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":[0.000630656,0.0009693506,0.0009267715,0.0004532725,0.0004786236,0.001187121,0.00119716,0.00127421,0.003783435],"category_scores_gemma":[0.003955924,0.0007042862,0.0008158152,0.000785767,0.000605716,0.001287372,0.00131313,0.0012805,0.00119858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003939913,"about_ca_system_score_gemma":0.001587979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002995993,"about_ca_topic_score_gemma":0.004735998,"domain_scores_codex":[0.9994105,0.0001509013,0.00003287876,0.0001051738,0.0002498241,0.00005070371],"domain_scores_gemma":[0.9988748,0.0005594385,0.0001453515,0.0001269509,0.0002605349,0.00003286167],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000168872,0.00008903497,0.0007424278,0.0002855593,0.000161898,0.0001365615,0.0006755647,0.6992423,0.03212565,0.06069344,0.002785919,0.2028928],"study_design_scores_gemma":[0.00001723594,0.00003000762,0.0001534766,0.00001285625,0.00001413363,0.00003209838,0.00003577191,0.9808944,0.005758862,0.01150146,0.001532199,0.00001747994],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006289328,0.00005354255,0.9919868,0.00005519025,0.00002202068,0.00002096511,0.00002174409,0.0002183639,0.001332069],"genre_scores_gemma":[0.2471502,0.0003016708,0.7413054,0.0001031734,0.00005945902,0.000211176,0.0002244018,0.0002836761,0.0103609],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003783435,"threshold_uncertainty_score":0.01265687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01244607554982687,"score_gpt":0.2367437615219746,"score_spread":0.2242976859721477,"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."}}