Informative input design for Kernel-Based system identification

• Published in: Automatica (Oxford) Vol. 89; pp. 37 - 43
• Main Authors: Fujimoto, Yusuke, Sugie, Toshiharu
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.03.2018
• Subjects: Bayesian estimation; Experiment design; Information theory; Kernel-Based system identification; Kernel-Based system identification; Experiment design; Bayesian estimation; Information theory

This paper discusses the design of input sequence for Kernel-Based system identification. From the Bayesian point of view, the kernel reflects a priori information about the target system, which implies that the information obtained from I/O data differs over kernels. This paper focuses on finding a...