The paper gives a survey of errors-in-variables methods in system identification.
Background and motivation are given, and examples illustrate why the identification problem …

This book presents an overview of the different errors-in-variables (EIV) methods that can be
used for system identification. Readers will explore the properties of an EIV problem. Such …

The paper gives an overview of errors-in-variables methods in system identification.
Background and motivation are given. Simple examples illustrate why the identification …

The errors-in-variables identification problem concerns dynamic systems whose input and
output variables are affected by additive noise. Several estimation methods have been …

This paper studies the linear dynamic errors-in-variables problem for filtered white noise
excitations. First, a frequency domain Gaussian maximum likelihood (ML) estimator is …

A system identification method for errors-in-variables problems based on covariance
matching was recently proposed. In the first step, a small amount of covariances of noisy …

In this paper, the problem of identifying stochastic linear continuous-time systems from noisy
input/output data is addressed. The input of the system is assumed to have a skewed …

In view of the fact that the output is only disturbed by error in most of the current system
studies, this article proposes a closed-loop variable system model with error (both input and …

The paper gives a survey of errors-in-variables methods in system identification.
Background and motivation are given, and examples illustrate why the identification problem …

An analysis of a covariance matching method for continuous-time errors-in-variables system
identification from discrete-time data is made. In the covariance matching method, the noise …