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Extrapolation and filtering of incomplete marker tracks by singular value decomposition (heart motion measurement)

机译:通过奇异值分解(心脏运动测量)外推和过滤不完整的标记轨迹

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The authors investigate whether the singular value decomposition (SVD) method can be modified to handle incomplete tracks such that appropriate extrapolations for incomplete marker tracks are obtained in an animal experiment were made incomplete by obscuring a part varying in length from 3% up to 44% of the observation time. Comparison of extrapolations with measurements results in a root mean square (RMS) error value of 0.25 pixel, where the total excursion of a marker is about 20 pixels. Using computer simulation data under similar conditions, the estimations were compared with the known signal values. The RMS error was found to be 1.2 sigma for the extrapolation in the obscured part and 0.7 sigma for the filtering in the observed part, where sigma /sup 2/ is the variance of the noise.
机译:作者研究了是否可以修改奇异值分解(SVD)方法以处理不完整的轨迹,从而通过遮盖长度从3%到44%的不同部分来使在动物实验中获得不完整标记轨迹的适当外推法不完整观察时间。将外推法与测量结果进行比较,得出的均方根(RMS)误差值为0.25像素,其中标记的总偏移量约为20像素。使用类似条件下的计算机模拟数据,将估计值与已知信号值进行比较。 RMS误差对于被遮挡部分的外推为1.2 sigma,对于观察部分的滤波为0.7 sigma,其中sigma / sup 2 /是噪声的方差。

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