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METHOD OF MULTI-SCALES INTRINSIC ENTROPY ANALYSIS

机译:多尺度内在熵分析方法

摘要

This invention discloses a multi-scales intrinsic entropy analysis method that can quantify the entropies on difference time scales for a complex time series. The implementation of the method decomposes a complex time series into a plurality of intrinsic mode functions by a nonlinear signal processing algorithm, such as the method of empirical mode decomposition. Then, the entropy increments can be calculated on multiple coarse-graining scales when an intrinsic mode functions is added into the reconstructed time series analyzed by the method of multi-scale entropy. The entropy increment is significant on a specific coarse-graining scale, which corresponds to the averaged period of the intrinsic mode functions. The entropy increment on the specific coarse-graining scale is defined as the intrinsic entropy for an intrinsic mode functions. Multiple intrinsic entropies represent the entropy properties for a complex time series on their corresponding time scales.
机译:本发明公开了一种多尺度固有熵分析方法,该方法可以对复杂时间序列的不同时间尺度上的熵进行量化。该方法的实现通过诸如经验模式分解的方法的非线性信号处理算法将复杂的时间序列分解为多个固有模式函数。然后,当将固有模式函数添加到通过多尺度熵方法分析的重构时间序列中时,可以在多个粗粒度尺度上计算熵增量。熵的增量在特定的粗粒度范围内很重要,它对应于本征模函数的平均周期。将特定粗粒度标度上的熵增量定义为本征模函数的本征熵。多个固有熵表示复杂时间序列在其相应时标上的熵属性。

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