{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/non-asymptotic-identification-of-lti-systems","title":"Non-asymptotic Identification of LTI Systems from a Single Trajectory","arxiv_id":"1806.05722","date":"2018-06-14","proceeding":null,"authors":["Samet Oymak","Necmiye Ozay"],"abstract":"We consider the problem of learning a realization for a linear time-invariant\n(LTI) dynamical system from input/output data. Given a single input/output\ntrajectory, we provide finite time analysis for learning the system's Markov\nparameters, from which a balanced realization is obtained using the classical\nHo-Kalman algorithm. By proving a stability result for the Ho-Kalman algorithm\nand combining it with the sample complexity results for Markov parameters, we\nshow how much data is needed to learn a balanced realization of the system up\nto a desired accuracy with high probability.","url_abs":"http://arxiv.org/abs/1806.05722v2","url_pdf":"http://arxiv.org/pdf/1806.05722v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"non-asymptotic-identification-of-lti-systems","repo_url":"https://github.com/zhengy09/SysId","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1806.05722","atlas_url":"https://app.syntology.ai/?focus=1806.05722","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}