{"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/system-identification-through-online-sparse","title":"System Identification through Online Sparse Gaussian Process Regression with Input Noise","arxiv_id":"1601.08068","date":"2016-01-29","proceeding":null,"authors":["Hildo Bijl","Thomas B. Schön","Jan-Willem van Wingerden","Michel Verhaegen"],"abstract":"There has been a growing interest in using non-parametric regression methods\nlike Gaussian Process (GP) regression for system identification. GP regression\ndoes traditionally have three important downsides: (1) it is computationally\nintensive, (2) it cannot efficiently implement newly obtained measurements\nonline, and (3) it cannot deal with stochastic (noisy) input points. In this\npaper we present an algorithm tackling all these three issues simultaneously.\nThe resulting Sparse Online Noisy Input GP (SONIG) regression algorithm can\nincorporate new noisy measurements in constant runtime. A comparison has shown\nthat it is more accurate than similar existing regression algorithms. When\napplied to non-linear black-box system modeling, its performance is competitive\nwith existing non-linear ARX models.","url_abs":"http://arxiv.org/abs/1601.08068v3","url_pdf":"http://arxiv.org/pdf/1601.08068v3.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":"system-identification-through-online-sparse","repo_url":"https://github.com/HildoBijl/SONIG","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"regression-1","task_name":"regression"}],"methods":[{"method_slug":"gaussian-process","method_name":"Gaussian Process"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1601.08068","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}