Unifying some higher-order statistic-based methods for errors-in-variables model identification Thil, Stephane; Zheng, Wei Xing; Gilson, Marion; ...

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Thil, Stephane ; Zheng, Wei Xing ; Gilson, Marion ; Garnier, Hugues
automaton; instrumental variable; higher-order statistics
In this paper, the problem of identifying linear discrete-time systems from noisy input and output data is addressed. Several existing methods based on higher-order statistics are presented. It is shown that they stem from the same set of equations and can thus be united from the viewpoint of extended instrumental variable methods. A numerical example is presented which confirms the theoretical results. Some possible extensions of the methods are then given.
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