@TechReport{	  it:2006-044,
  author	= {Mei Hong and Torsten S{\"o}derstr{\"o}m and Johan
		  Schoukens and Rik Pintelon},
  title		= {Comparison of Time Domain Maximum Likelihood Method and
		  Sample Maximum Likelihood Method in Errors-in-Variables
		  Identification},
  institution	= {Department of Information Technology, Uppsala University},
  department	= {Division of Systems and Control},
  year		= {2006},
  number	= {2006-044},
  month		= sep,
  abstract	= {The time domain maximum likelihood (TML) method and the
		  Sample Maximum Likelihood (SML) method are two general
		  approaches for identifying errors-in-variables models. In
		  the TML method, an important assumption is that the
		  noise-free input signal must be a stationary process with
		  rational spectrum. For SML, the noise-free input need to be
		  periodic. In this report, numerical comparisons of these
		  two methods are done under different situations. The
		  results suggest that TML and SML have similar estimation
		  accuracy at moderate or high signal-to-noise ratio (SNR).}
}