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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Dunne, B.E. Williamson, G.A. |
| Copyright Year | 2003 |
| Description | Author affiliation: Padnos Sch. of Eng., Grand Valley State Univ., Grand Rapids, MI, USA (Dunne, B.E.; Williamson, G.A.) |
| Abstract | In a variety of nonlinear system identification applications, a bilinear model form is suitable to model the dynamics of the system. In such situations, parameter estimates are biased when an equation error framework under the least squares (LS) performance criterion is used in the presence of output measurement noise. In this paper an iterative approach to bilinear system adaptation is considered that yields unbiased parameter estimates in certain signal environments. The unbiasedness is achieved by using a mixed LS-total least squares (TLS) criterion and applying an algorithm recently developed by the authors. The performance is illustrated via simulation. |
| Starting Page | 591 |
| Ending Page | 595 |
| File Size | 282745 |
| Page Count | 5 |
| File Format | |
| ISBN | 0780381041 |
| DOI | 10.1109/ACSSC.2003.1291979 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2003-11-09 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | System identification Nonlinear equations Nonlinear systems Parameter estimation Nonlinear dynamical systems Least squares approximation Noise measurement Working environment noise Iterative methods Yield estimation |
| Content Type | Text |
| Resource Type | Article |
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