Abstract
The paper presents a set of new non-parametric and parametric identification algorithms oriented to using within the input/output system description. A purpose of elaborating the identification techniques is to involve as broad as possible, to some extend, classes of stochastic system descriptions, both linear and nonlinear ones, assuming that the lack of knowledge with respect to the system may vary from unknown system parameters to unknown system structure at all.
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Chernyshov, K., Pashchenko, F. (2000). An Identification Algorithmic Toolkit for Intelligent Control Systems. In: Kopacek, P., Moreno-DÃaz, R., Pichler, F. (eds) Computer Aided Systems Theory - EUROCAST’99. EUROCAST 1999. Lecture Notes in Computer Science, vol 1798. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10720123_49
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DOI: https://doi.org/10.1007/10720123_49
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-67822-9
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