{"id":"W2140494646","doi":"10.1109/acssc.1996.599176","title":"SVD-updating via constrained perturbations with application to subspace tracking","year":2002,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Singular value decomposition; Subspace topology; Singular value; Ode; Orthonormality; Algorithm; Mathematics; Signal subspace; Ordinary differential equation; Singular perturbation; Matrix decomposition; Computer science; Applied mathematics; Noise (video); Differential equation; Orthonormal basis; Artificial intelligence; Mathematical analysis; Eigenvalues and eigenvectors","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":[0.0008235156,0.0009689489,0.001085746,0.0006217589,0.0003894914,0.000874974,0.001089744,0.0009627559,0.001224066],"category_scores_gemma":[0.003457732,0.0004954729,0.0006371873,0.001041823,0.000909299,0.001513631,0.001278701,0.001199061,0.0007025031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004285372,"about_ca_system_score_gemma":0.0007614336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002406068,"about_ca_topic_score_gemma":0.00197728,"domain_scores_codex":[0.9993359,0.0001802412,0.00005105149,0.0001168807,0.0002770667,0.00003869201],"domain_scores_gemma":[0.9987468,0.0005136948,0.0001249603,0.0001950273,0.000365895,0.00005361201],"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":[0.0001948009,0.00007310911,0.0005741145,0.0001711003,0.00008755065,0.00009866328,0.0001444386,0.5317392,0.0293487,0.0496779,0.002653261,0.3852371],"study_design_scores_gemma":[0.000005472709,0.00003088186,0.00004302214,0.000003449765,0.000004380986,0.00002716744,0.000004610127,0.9894769,0.004442932,0.004653771,0.001297618,0.000009787115],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001432686,0.0000731632,0.9980636,0.00003163165,0.00002936118,0.00001019254,0.000009529597,0.0001552876,0.0001944651],"genre_scores_gemma":[0.07403109,0.0003722489,0.9235891,0.00005922394,0.0001064501,0.000110844,0.0001114869,0.0001232999,0.001496193],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002406068,"threshold_uncertainty_score":0.004784107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01524764421882584,"score_gpt":0.2479898889619146,"score_spread":0.2327422447430887,"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."}}