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IMA Journal of Mathematical Control and Information 1988 5(4):309-313; doi:10.1093/imamci/5.4.309
© 1988 by Institute of Mathematics and its Applications
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On-line Identification of Time-varying Processes at Various Signal-to-Noise Ratios

M. A. FKIRIN

Department of Automatic Control and Measurements, Faculty of Electronic Engineering Menoufia University Menouf, Egypt

New results in the on-line identification of time-varying dynamic processes are presented. The performance of the weighted least-squares identification algorithm, for different values of signal-to-noise ratio (SNR), is investigated with reference to artificial records from Monte Carlo tests. It is obvious that a higher SNR will result in a good estimated model. This paper discusses whether it stays as easy at low SNR to find the model structure accurately as it is at high SNR.


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