| 1. |
- Akçay, Hüseyin, et al.
(författare)
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On the Choice of Norms in System Identification
- 1994
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Ingår i: Proceedings of the 10th IFAC Symposium on System Identification. - Linköping : Linköping University. - 9780080422251 ; , s. 103-108
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- In this paper we discuss smooth and sensitive norms for prediction error system identification when the disturbances are magnitude bounded. Formal conditions for sensitive norms, which give an order of magnitude faster convergence of the parameter estimate variance, are developed. However, it also is shown that the parameter estimate variance convergence rate of sensitive norms is arbitrarily bad for certain distributions. A necessary condition for a norm to be statistically robust with respect to the family F(C) of distributions with support [-C, C] for some arbitrary C>0 is that its second derivative does not vanish on the support. A direct consequence of this observation is that the quadratic norm is statistically robust among all lp-norms, p⩽2<∞ for F(C).
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| 2. |
- Akçay, Hüseyin, et al.
(författare)
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The Least-Squares Identification of FIR Systems Subject to Worst-Case Noise
- 1994
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Ingår i: Proceedings of the 10th IFAC Symposium on System Identification. - Linköping : Linköping University. - 9780080422251 ; 23:5, s. 329-338
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The least-squares identification of FIR systems is analyzed assuming that the noise is a bounded signal and the input signal is a pseudo-random binary sequence. A lower bound on the worst-case transfer function error shows that the least-square estimate of the transfer function diverges as the order of the FIR system is increased. This implies that, in the presence of the worst-case noise, the trade-off between the estimation error due to the disturbance and the bias error (due to unmodeled dynamics) is significantly different from the corresponding trade-off in the random error case: with a worst-case formulation, the model complexity should not increase indefinitely as the size of the data set increases.
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| 3. |
- Andersson, Torbjörn, et al.
(författare)
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Identification Aspects of Inter-Sample Input Behavior
- 1994
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Ingår i: Proceedings of the 10th IFAC Symposium on System Identification. - Linköping : Linköping University. - 9780080422251 ; , s. 137-142
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Konferensbidrag (refereegranskat)abstract
- In this contribution aspects of inter-sample input signal behavior are examined. The starting point is that parametric identification always is performed on basis of discrete-time data. This is valid for identification of discrete-time models as well as continuous-time models. The usual assumptions on the input signal are; i) it is band-limited, ii) it is piecewise constant or iii) it is piecewise linear. One point made in this paper is that if a discrete-time model is used, the best possible (in the model structure) adjustment to data is made. This is independent of the assumption on the input signal. However, a transformation of the obtained discrete model to a continuous one is not possible without additional assumptions on the input signal. The other point made is that the frequency functions of the discrete models very well coincides with the frequency functions of the discretized continuous time models and the continuous time transfer function fitted in the frequency domain.
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| 4. |
- Gunnarsson, Svante
(författare)
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On Covariance Modification and Regularization in Recursive Least Squares Identification
- 1994
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Ingår i: Proceedings of the 10th IFAC Symposium on System Identification. - 9780080422251 ; , s. 661-666
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Konferensbidrag (refereegranskat)abstract
- In this paper the relationships between covariance modification and regularization in recursive least squares identification are investigated. An update equation for the information matrix is derived and it is shown how regularization of the information matrix can be expressed as a particular type of covariance matrix modification. The paper also presents an analysis of the effects of a covariance modification for obtaining regularization that was proposed in Salgado et al. (1988)
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| 5. |
- Hjalmarsson, Håkan, 1962-, et al.
(författare)
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A Unifying View of Disturbances in Identification
- 1994
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Ingår i: Proceedings of the 10th IFAC Symposium on System Identification. - Linköping : Linköping University. - 9780080422251 ; , s. 73-78
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Konferensbidrag (refereegranskat)
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| 6. |
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| 7. |
- Ljung, Lennart, 1946-, et al.
(författare)
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A Study of some Approaches to Vibration Data Analysis
- 1994
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Ingår i: Proceedings of the 10th IFAC Symposium on System Identification. - 9780080422251 ; , s. 289-294
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Konferensbidrag (refereegranskat)abstract
- Using data from extensive vibrational tests of the new aircraft Saab 2000 three different methods for vibration analysis are studied. These methods are ERA (eigensystem realization algorithm), N4SID (a subspace method) and PEM (prediction error approach). We find that both the ERA and N4SID methods give good initial model parameter estimates that can be further improved by the use of PEM. We also find that all methods give good insights into the vibrational modes.
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| 8. |
- Ljung, Lennart, 1946-, et al.
(författare)
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Comparison of Three Classes of Identification Methods
- 1994
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Ingår i: Proceedings of the 10th IFAC Symposium on System Identification. - Linköping : Linköping University. - 9780080422251 ; , s. 175-180
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Rapport (övrigt vetenskapligt/konstnärligt)
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| 9. |
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| 10. |
- Ljung, Lennart, 1946-, et al.
(författare)
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Tools for Semi-Physical Modeling
- 1994
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Ingår i: Proceedings of the 10th IFAC Symposium on System Identification. - 9780080422251 ; , s. 237-242
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Konferensbidrag (refereegranskat)abstract
- By semi-physical modeling we mean such an application of system identification, where physical insight into the application is used to come up with suitable nonlinear transformations of the raw measurements, so as to allow for a good model structure. Semi-physical modeling is less "ambitious" than physical modeling, in that no complete physical structure is sought, just suitable inputs and outputs that can be subjected to more or less standard model structures, such as linear regressions. In this contribution we discuss various tools that can support the process of semi-physical modeling. We will deal both with analytical tools such as differential algebra and more informal ones such as the programming environment.
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