Fixed‐order optimal deconvolution filter with irregular missing data
Fixed‐order optimal deconvolution filter with irregular missing data
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DOI：
10.1002/acs.1133
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发表时间：
2010-04
影响因子：
3.1
通讯作者：
J. Hung
中科院分区：
文献类型：
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作者：
J. Hung
通常，常规去卷积滤波器的重建性能由于缺失数据而恶化。本文提出了一种固定阶数反卷积滤波器的设计方法，用于从具有不规则缺失数据的接收信号中重建信号。缺失数据模型基于概率结构。缺失数据的发生概率是未知的先验。在这种情况下，反卷积滤波器的设计问题变成了一个复杂的非线性估计问题。在本研究中，提出一种基于遗传算法的设计方法来处理不规则缺失数据的信号重构设计问题。最后，给出了两个例子来说明所提出的反卷积滤波器的仿真结果。结果表明，如果在反卷积滤波器设计过程中考虑了丢失概率，重构性能将得到显著改善。版权所有© 2009约翰威利父子有限公司。
In general, the reconstruction performance of the conventional deconvolution filter is deteriorated by the missing data. In this paper, a fixed‐order deconvolution filter design method is proposed for the signal reconstruction from received signal with irregular missing data. The missing data model is based on a probabilistic structure. The probability of occurrence of missing data is unknown a prior. In this situation, the deconvolution filter design problem becomes a complicated nonlinear estimation problem. In this study, a design method based on genetic algorithms is proposed to treat the signal reconstruction design problem with irregular missing data. Finally, two examples are given to illustrate the simulation results of the proposed deconvolution filter. The results show that the reconstruction performance is improved significantly if the missing probability is considered in the deconvolution filter design procedure. Copyright © 2009 John Wiley & Sons, Ltd.