Abstract
In this paper, we present a noisy version of the algebraic geometric approach of identifying parameters of discrete-time linear hybrid system. Two approximate ways of estimating hybrid parameters are considered: one is using MSE criteria, while the other is based on the information divergence that measures the distance between the error probability density function (PDF) of the identified model and the desired error PDF. A stochastic information divergence gradient algorithm is derived for the identification problem of non-gaussian system.
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Pu, L., Hu, J., Chen, B. (2008). Information Theoretical Approach to Identification of Hybrid Systems. In: Egerstedt, M., Mishra, B. (eds) Hybrid Systems: Computation and Control. HSCC 2008. Lecture Notes in Computer Science, vol 4981. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78929-1_56
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DOI: https://doi.org/10.1007/978-3-540-78929-1_56
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-78928-4
Online ISBN: 978-3-540-78929-1
eBook Packages: Computer ScienceComputer Science (R0)