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Improving Empirical Mode Decomposition based on up-sampling

机译:基于上采样改善经验模式分解

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The paper proposes an improved Empirical Mode Decomposition method based on up-sampling, due to the energy leakage in traditional Empirical Mode Decomposition for insufficient sampling rate(digital domain frequency greater than 0.2). The method uses the signal interpolation to improve sampling rate before EMD, and then recovers the original scale by corresponding down-sampling and low pass filtering. The numerical results show that it can partly recover the accurate position of extreme points and effectively reduce the energy leakage. Three typical interpolations are also employed and the result shows that the effect of using cubic spline interpolation with 4 times is the best relatively.
机译:由于传统的经验模式分解中由于采样率不足(数字域频率大于0.2)而导致的能量泄漏,因此提出了一种基于上采样的改进的经验模式分解方法。该方法使用信号插值来提高EMD之前的采样率,然后通过相应的下采样和低通滤波来恢复原始比例。数值结果表明,该算法可以部分恢复极端点的精确位置,有效地减少了能量的泄漏。还采用了三种典型的插值方法,结果表明,使用三次三次样条插值的效果最好。

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