@TechReport{	  it:2001-006,
  author	= {Erik K. Larsson and Torsten S{\"o}derstr{\"o}m},
  title		= {Identification of Continuous-Time {AR} Processes by Using
		  Limiting Properties of Sampled Systems},
  institution	= {Department of Information Technology, Uppsala University},
  department	= {Division of Systems and Control},
  year		= {2001},
  number	= {2001-006},
  month		= mar,
  abstract	= {Consider the problem of estimating the parameters in a
		  continuous-time autoregressive (CAR) model from
		  discrete-time samples. In this paper a simple and
		  computationally efficient method is introduced, and
		  analyzed with respect to bias distribution. The approach is
		  based on replacing the derivatives by delta approximations,
		  forming a linear regression, and using the least squares
		  method. It turns out that consistency can be assured by
		  applying a particular prefilter to the data; a filter that
		  is easy to compute and is only dependent on the order of
		  the continuous-time system. As a side effect several
		  general properties for discrete-time autoregressive moving
		  average (ARMA) systems originating from sampled
		  CAR-processes will also be presented. Finally, the
		  introduced method is compared to other methods in some
		  simulation studies. }
}