{"paper":{"title":"State estimation under non-Gaussian Levy noise: A modified Kalman filtering method","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IT","cs.LG","math.IT","math.PR","stat.ML"],"primary_cat":"math.DS","authors_text":"Jinqiao Duan, Xiangjun Wang, Xiaofan Li, Xu Sun","submitted_at":"2013-03-10T23:20:12Z","abstract_excerpt":"The Kalman filter is extensively used for state estimation for linear systems under Gaussian noise. When non-Gaussian L\\'evy noise is present, the conventional Kalman filter may fail to be effective due to the fact that the non-Gaussian L\\'evy noise may have infinite variance. A modified Kalman filter for linear systems with non-Gaussian L\\'evy noise is devised. It works effectively with reasonable computational cost. Simulation results are presented to illustrate this non-Gaussian filtering method."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1303.2395","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}