Abstract
An algorithm for designing conditional regression models of nonlinear dynamic systems is described. The complexity of the model is evaluated using the properties of data digital representation. The identification algorithm automatically chooses a structure for a system. Algorithms for complete and incomplete experiments are described. An example is given.
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Chadeev, V.M. Digital Identification of Nonlinear Dynamic Systems. Automation and Remote Control 65, 1938–1945 (2004). https://doi.org/10.1023/B:AURC.0000049878.08882.21
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DOI: https://doi.org/10.1023/B:AURC.0000049878.08882.21