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Nonparametric kernel algorithm for recovery of functions from noisy measurements with applications. (English) Zbl 0564.93071
This note presents a kernel algorithm for recovery of a regression function from noisy data. Conditions are provided that assure pointwise convergence in the mean square and almost sure senses. An application to a class of linear system identification problems is discussed.

MSC:
93E25 Computational methods in stochastic control (MSC2010)
93C05 Linear systems in control theory
93E12 Identification in stochastic control theory
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