Optimal deconvolution based on polynomial methods
Optimal deconvolution based on polynomial methods
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DOI：
10.1109/29.21684
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发表时间：
1989-02
期刊：
影响因子：
--
通讯作者：
A. Ahlén;M. Sternad
中科院分区：
文献类型：
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作者：
A. Ahlén;M. Sternad
估计已知线性系统的输入的问题在移位算子多项式公式中处理。均方估计误差被最小化。输入和彩色测量噪声由独立的 ARMA（自回归移动平均）过程描述。通过执行谱分解并求解多项式方程来计算滤波器。该方法可应用于输入预测、滤波和平滑问题以及二次准则中预滤波器的使用。它适用于非最小相位以及不稳定系统，如两个示例所示。 >
The problem of estimating the input to a known linear system is treated in a shift operator polynomial formulation. The mean-square estimation error is minimized. The input and a colored measurement noise are described by independent ARMA (autoregressive moving average) processes. The filter is calculated by performing a spectral factorization and solving a polynomial equation. The approach can be applied to input prediction, filtering, and smoothing problems as well as to the use of prefilters in the quadratic criterion. It applies to nonminimum-phase as well as unstable systems, as illustrated by two examples. >