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Noise Reduction, Atmospheric Pressure Admittance Estimation and Long-Period Component Extraction in Time-Varying Gravity Signals Using Ensemble Empirical Mode Decomposition

机译：基于集合经验模式分解的时变重力信号的降噪，大气压导纳估计和长周期分量提取

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Linsong Wang; Chao Chen; Jinsong Du; and Qing Liang;
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年度 2015
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1. Noise Reduction, Atmospheric Pressure Admittance Estimation and Long-Period Component Extraction in Time-Varying Gravity Signals Using Ensemble Empirical Mode Decomposition [J] . Wang Linsong, Chen Chao, Du Jinsong, TAO: Terrastrial, atmospheric, and oceanic sciences . 2015,第2aPta1期

机译：时空重力信号的组合经验模态分解，降噪，大气压导纳估计和长期分量提取
2. A novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise, minimum mean square variance criterion and least mean square adaptive filter [J] . Yu-xing Li, Long Wang 兵工学报（英文版） . 2020,第003期
3. Blind source extraction of acoustic emission signals for rail cracks based on ensemble empirical mode decomposition and constrained independent component analysis [J] . Measurement . 2020,第期

机译：基于集合经验模式分解的轨裂声对声发射信号的盲源提取和约束独立分量分析
4. ATMOSPHERIC LIDAR NOISE REDUCTION BASED ON ENSEMBLE EMPIRICAL MODE DECOMPOSITION [C] . Jun LI, Wei GONG, Yingying Ma Imaging a Sustainable Future . 2012

机译：基于集合经验模式分解的大气激光乐降噪
5. Investigation of probabilistic principal component analysis compared to proper orthogonal decomposition methods for basis extraction and missing data estimation. [D] . Lee, Kyunghoon. 2010

机译：比较概率主成分分析与适当的正交分解方法进行基础提取和数据丢失估计。
6. Estimation of Heart Rate and Respiratory Rate from PPG Signal Using Complementary Ensemble Empirical Mode Decomposition with both Independent Component Analysis and Non-Negative Matrix Factorization [O] . Ruisheng Lei, Bingo Wing-Kuen Ling, Peihua Feng, 2020

机译：使用独立分量分析和非负矩阵分解的互补集合经验模式分解从PPG信号估计心率和呼吸率
7. ATMOSPHERIC LIDAR NOISE REDUCTION BASED ON ENSEMBLE EMPIRICAL MODE DECOMPOSITION [O] . J. Li, W. Gong, Y. Ma 2012

机译：基于集合经验模态分解的大气激光降噪

Noise Reduction, Atmospheric Pressure Admittance Estimation and Long-Period Component Extraction in Time-Varying Gravity Signals Using Ensemble Empirical Mode Decomposition

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