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Recovering Method of Missing Data Based on Proposed Modified Kalman Filter When Time Series of Mean Data is Known

机译：当已知平均数据的时间序列时，基于改进卡尔曼滤波的缺失数据恢复方法

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Kohei Arai;
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年度 2013
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1. Generalized unscented Kalman filtering based radial basis function neural network for the prediction of ground radioactivity time series with missing data [J] . 伍雪冬, 王耀南, 刘维亭, 中国物理：英文版 . 2011,第006期

机译：基于广义无味卡尔曼滤波的径向基函数神经网络预测缺少数据的地面放射性时间序列
2. Generalized unscented Kalman filtering based radial basis function neural network for the prediction of ground radioactivity time series with missing data [J] . Wu Xue-Dong, Wang Yao-Nan, Liu Wei-Ting, 中国物理：英文版 . 2011,第006期

机译：基于广义无味卡尔曼滤波的径向基函数神经网络预测缺少数据的地面放射性时间序列
3. A MATLAB-based Kriged Kalman Filter software for interpolating missing data in GNSS coordinate time series [J] . Ning Liu, Wujiao Dai, Rock Santerre, GPS Solutions . 2018,第1期

机译：基于MATLAB的Kriged卡尔曼滤波器软件，用于在GNSS坐标时间序列中插值缺失数据
4. ICA AND NONLINEAR TIME SERIES PREDICTION FOR RECOVERING MISSING DATA SEGMENTS IN MULTIVARIATE SIGNALS [C] . Torbjorn Eltoft, Orjan Kristiansen 3rd International Conference on Independent Component Analysis and Signal Separation; Dec 9-13, 2001; San Diego, California . 2001

机译：多变量信号中丢失数据段的ICA和非线性时间序列预测
5. A multivariate time series analysis based on frequency domain decomposition and Hilbert space projection in the presence of missing data. [D] . Iasonos, Alexia Elia. 2002

机译：在缺少数据的情况下，基于频域分解和希尔伯特空间投影的多元时间序列分析。
6. Spatial-Temporal Congestion Identification Based on Time Series Similarity Considering Missing Data [O] . Hongsheng Qi, Meiqi Liu, Dianhai Wang, -1

机译：考虑时间序列相似性的时空拥塞识别
7. Prediction Methods for Time Series Data with Many Missing Data Based on RLS Method. [O] . Kaname SETO, Kohei ARAI 1999

机译：基于RLS方法的许多缺失数据的时间序列数据预测方法。
8. Kalman Filter Time Series Analysis of Gamma-Ray Data from NaI(T1) Detectors for the ND6620 Computer. [R] . Phillips, G. W. 1985

机译：ND6620计算机NaI（T1）探测器伽马射线数据的卡尔曼滤波时间序列分析。

Recovering Method of Missing Data Based on Proposed Modified Kalman Filter When Time Series of Mean Data is Known

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