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For the input-output representation of non-uniformly multirate discrete-time systems, a coupled least squares algorithm is derived to estimate the model parameters with the advantage of avoiding the computation of matrix inversion. Moreover, The proposed algorithm has good convergence properties. The simulation test verifies the effectiveness of the algorithm.
In this paper, a filtering based recursive least squares algorithm is derived for identification of the non-uniformly sampled Box-Jenkins systems. The basic idea is to use an estimated noise transfer function to filter the input-ouput data, to obtain two identification models containing the parameters of the system model and the noise model respectively, and to present the filtering based recursive...
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