Efficient Estimation of Errors-in-Variables Models

نویسندگان

  • István Vajk
  • Jenő Hetthéssy
چکیده

The paper addresses the discrete-time linear process identification problem assuming noisy input and output records available for the parameter estimation. The efficient algorithms are derived for the simultaneous estimation of the process and noise parameters. Implementation techniques based on matrix and polynomial decompositions are given in details resulting in estimation algorithms with reduced computation demand. The presented algorithms deliver the parameter estimation in an iterative way as a result of a generalized eigenvalue-eigenvector or a generalized singular value decomposition.

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تاریخ انتشار 2008