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A technique for the identification of linear systems

Steiglitz, K., McBride, L.·1965·IEEE Transactions on Automatic Control

Abstract

An iterative technique is proposed to identify a linear system from samples of its input and output in the presence of noise by minimizing the mean-square error between system and model outputs. The model chosen has a transfer function which is a ratio of polynomials in z-1. Although the regression equations for the optimal set of coefficients are highly nonlinear and intractable, it is shown that the problem can be reduced to the repeated solution of a related linear problem. Computer simulation of a number of typical discrete systems is used to demonstrate the considerable improvement over the Kalman estimate which can be obtained in a few iterations. The procedure is found to be effective at signal-to-noise ratios less than unity, and with as few as 200 samples of the input and output records.

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Metadata

Authors
Steiglitz, K., & McBride, L.
Venue
IEEE Transactions on Automatic Control
Published
1965-10
Volume
10
Issue
4
Pages
461-464
ISSN
0018-9286 (ISSN-L)
OpenAlex
W2021123050
Cited by
641
References
0
FWCI
15.21
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A technique for the identification of linear systems. https://app.cochat.ai/papers/10.1109/tac.1965.1098181
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Steiglitz, K., & McBride, L. (1965). A technique for the identification of linear systems. IEEE Transactions on Automatic Control. https://doi.org/10.1109/tac.1965.1098181

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