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Convergence analysis of estimation algorithms for dual-rate stochastic systems. (English) Zbl 1095.65056

First, a deterministic system described by a difference equation is considered. Using a polynomial transformation technique, a dual-rate model is derived. Based on this model, a recursive least squares algorithm is proposed to estimate the parameters and the intersample outputs. The algorithm uses only dual-rate measurement data. Next, a martingale process is formulated. Using the stochastic process theory, the convergence of the parameter estimation given by the proposed algorithm is proved. Two illustrative examples are also presented.

MSC:

65K10 Numerical optimization and variational techniques
93E10 Estimation and detection in stochastic control theory
93E12 Identification in stochastic control theory
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