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A technique for the identification of linear systems
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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Cited by
An iterative method for the identification of nonlinear systems using a Hammerstein model
Narendra, K., & Gallman, P. (1966) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1966.1098387 · Cited by 699
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Valimaki, V., Parker, J. D., Savioja, L., Smith, J. O., & Abel, J. S. (2012) · IEEE Transactions on Audio, Speech, and Language Processing · doi:10.1109/tasl.2012.2189567 · Cited by 213
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Chu, P., Muller, R., Koralek, A., Carmena, J. M., Rabaey, J. M., & Gambini, S. (2013) · 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2013.6609483 · Cited by 13
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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