Abstract
We study the performance of system identification methods on a finite data sample. Our results are of the following form: with a probability not less than 1-/spl delta/, minimising the empirical identification cost leads to an estimate which is within an accuracy /spl epsiv/ from the theoretical optimal estimate. Explicit expressions for the accuracy /spl epsiv/ are derived, revealing its dependence on the data generation characteristics and the choices made in the system identification procedure. This paper presents a finite sample identification theory applicable to a general linear time-invariant setting.
Full Text 
Sign-in/Register to access full text options
Sign-in/Register to access full text options 
Published version (
Free)
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
