A shift in paradigm for system identification. Issue 2 (1st February 2020)

• Record Type: Journal Article
• Authors: Ljung, Lennart; Chen, Tianshi; Mu, Biqiang
• Is Part Of: International journal of control. Volume 93:Issue 2(2020)
• Page Start: 173
• Page End: 180
• Publication Date: 2020-02-01
• Subjects: System identification -- linear regressions -- bias-variance tradeoff -- regularisation -- kernel methods; Automatic control -- Periodicals; Electronic journals; 629.8
• DOI: 10.1080/00207179.2019.1578407
• Languages: English
• ISSNs: 0020-7179

Abstract

ABSTRACT: System identification is a mature research area with well established paradigms, mostly based on classical statistical methods. Recently, there has been considerable interest in so called kernel-based regularisation methods applied to system identification problem. The recent literature on this is extensive and at times difficult to digest. The purpose of this contribution is to provide an accessible account of the main ideas and results of kernel-based regularisation methods for system identification. The focus is to assess the impact of these new techniques on the field and traditional paradigms.