Abstract
Abstract When all observed variables are affected by noise, parameter estimation is known as the errors in variables problem. So far parameter bounding methods and algorithms have been developed on the assumption that the regressor variables are exactly known. In this paper, the problem of parameter bounding in the case of linear systems with bounded errors in variables is addressed. Necessary and sufficient condition for a concise description of the feasible parameter set is given. Topological features of the feasible parameter region, such as convexity and connectedness, are discussed with the help of a two-dimensional example.
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