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This chapter discusses the LPTV system parametric identification using a block approach. An block algorithm is proposed for optimal estimation of the parameters of LPTV system from the input sequence and the output sequence corrupted by additive noise with Gaussian distribution. In the proposed method the LS error criterion has been used. The algorithm provides a useful computational tool based on an appropriate theoretical foundation for parameter estimation of LTI systems from input and output data. Simulation results are presented that demonstrate the performance of the approach.

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Optimal Parametric Identification of Linear Periodically Time-Variant Systems

  • 章节

  • 发表日期：

    2026年

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  • Rimantas Pupeikis,
  • Kazys Kazlauskas

摘要

This chapter discusses the LPTV system parametric identification using a block approach. An block algorithm is proposed for optimal estimation of the parameters of LPTV system from the input sequence and the output sequence corrupted by additive noise with Gaussian distribution. In the proposed method the LS error criterion has been used. The algorithm provides a useful computational tool based on an appropriate theoretical foundation for parameter estimation of LTI systems from input and output data. Simulation results are presented that demonstrate the performance of the approach.