Estimation of a signal waveform from noisy data using low-rank approximation to a data matrix
Estimation of a signal waveform from noisy data using low-rank approximation to a data matrix
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DOI：
10.1109/78.212753
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发表时间：
1993-04
期刊：
影响因子：
--
通讯作者：
D. Tufts;A. A. Shah-A.
中科院分区：
文献类型：
--
作者：
D. Tufts;A. A. Shah-A.
对一种数据自适应信号估计算法进行了分析和改进。通过对降阶数据矩阵的摄动分析来揭示其统计性质。将获得的信息用于计算D. Tufts et al.（1982）的Toeplitz-restoration算法的性能。这种分析导致了方法的改进，并通过仿真和与Cramer-Rao边界的比较证明了预测的改进。>
An analysis and improvement of a data-adaptive signal estimation algorithm are presented. Perturbation analysis of a reduced-rank data matrix is used to reveal its statistical properties. The obtained information is used for calculating the performance of the Toeplitz-restoration algorithm of D. Tufts et al. (1982). This analysis leads to improvements of the methods, and the predicted improvements are demonstrated by simulation and comparison with the Cramer-Rao bounds. >