Kernel Identification of Non-Linear Systems with General Structure
Autor: | Zygmunt Hasiewicz, Grzegorz Mzyk, Paweł Mielcarek |
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Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
0209 industrial biotechnology
lcsh:T55.4-60.8 Computer science wiener system 02 engineering and technology Least squares lcsh:QA75.5-76.95 Theoretical Computer Science 020901 industrial engineering & automation 0202 electrical engineering electronic engineering information engineering lcsh:Industrial engineering. Management engineering system identification non-parametric methods Numerical Analysis Model selection System identification hammerstein system Parameter identification problem Computational Mathematics Nonlinear system Computational Theory and Mathematics Kernel (statistics) kernel regression Kernel regression 020201 artificial intelligence & image processing lcsh:Electronic computers. Computer science Algorithm Curse of dimensionality |
Zdroj: | Algorithms, Vol 13, Iss 328, p 328 (2020) Algorithms Volume 13 Issue 12 |
ISSN: | 1999-4893 |
Popis: | In the paper we deal with the problem of non-linear dynamic system identification in the presence of random noise. The class of considered systems is relatively general, in the sense that it is not limited to block-oriented structures such as Hammerstein or Wiener models. It is shown that the proposed algorithm can be generalized for two-stage strategy. In step 1 (non-parametric) the system is approximated by multi-dimensional regression functions for a given set of excitations, treated as representative set of points in multi-dimensional space. &lsquo Curse of dimensionality problem&rsquo is solved by using specific (quantized or periodic) input sequences. Next, in step 2, non-parametric estimates can be plugged into least squares criterion and support model selection and estimation of system parameters. The proposed strategy allows decomposition of the identification problem, which can be of crucial meaning from the numerical point of view. The &ldquo estimation points&rdquo in step 1 are selected to ensure good task conditioning in step 2. Moreover, non-parametric procedure plays the role of data compression. We discuss the problem of selection of the scale of non-parametric model, and analyze asymptotic properties of the method. Also, the results of simple simulation are presented, to illustrate functioning of the method. Finally, the proposed method is successfully applied in Differential Scanning Calorimeter (DSC) to analyze aging processes in chalcogenide glasses. |
Databáze: | OpenAIRE |
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