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New method for determining common optimal parameters m and r of approximate entropy and sample entropy

A technology of optimal parameters and sample entropy, applied in electrical digital data processing, special data processing applications, instruments, etc., can solve problems such as constraints, and achieve the effects of good applicability, accurate calculation results, and simple and easy-to-operate methods.

Inactive Publication Date: 2017-05-31
LANZHOU UNIVERSITY
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Problems solved by technology

However, there is currently no effective method to determine the common optimal parameters m and r of the approximate entropy and sample entropy of the same research object, which largely restricts the application of these two complexity measures

Method used

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  • New method for determining common optimal parameters m and r of approximate entropy and sample entropy
  • New method for determining common optimal parameters m and r of approximate entropy and sample entropy
  • New method for determining common optimal parameters m and r of approximate entropy and sample entropy

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Embodiment example

[0037] The present invention takes the monthly runoff of the guide hydrological station in the upper reaches of the Yellow River from 1960 to 1990 and the surface average monthly precipitation of the watershed above the guide hydrological station as the research object, and the setting parameter m is 2~6, and the parameter r is 0.01~1.5SD, wherein SD is the standard deviation of the sequence, and the step size is taken as 0.01. Calculate the approximate entropy and sample entropy of runoff and precipitation under different parameters m and r scenarios, and calculate the two complexities of runoff or precipitation sequences under different parameters m The common optimal parameter r value, and then based on the sum of the correlation coefficient and the absolute value of the correlation coefficient, determine the common optimal parameter m and r values ​​of the approximate entropy and sample entropy applicable to runoff and precipitation.

[0038] For the results, see respective...

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Abstract

The invention relates to a new method for determining the common optimal parameters m and r of approximate entropy and sample entropy. The new method comprises the following steps: 1, setting different situations of parameters m and r of approximate entropy and sample entropy of a time sequence; 2, calculating an approximate entropy value and a sample entropy value of the parameters m and r in the different situations; 3, determining the common optimal parameter r of the approximate entropy and the sample entropy of different parameters m in certain time sequences; 4, determining the common optimal parameters m and r of the approximate entropy and the sample entropy of all the time sequences based on a correlation coefficient and the sum of absolute values thereof. The method guarantees the consistency of two different complexity measurement results, and theoretically solves the problem that the inconsistency of the approximate entropy value and the sample entropy value is caused by the different parameters m and r; the method is simple and easy to operate, high in computational efficiency, and more accurate and scientific in calculation results, is both suitable for a single research object and multiple research objects, and has important theoretical significance and practical value, thus being wide in application prospect.

Description

technical field [0001] The invention relates to the field of complexity measurement, in particular to a new method for determining common optimal parameters m and r of approximate entropy and sample entropy. Background technique [0002] The concept of entropy is derived from thermodynamics and represents the portion of energy that cannot be used to do work. Entropy is often used to describe the complexity of time series, and has been directly or indirectly applied to economics, social sciences, geosciences, life sciences, engineering, information science, mathematics and other disciplines and has made important research progress. Among them, Kolmogorov–Sinai entropy is a widely used entropy. As the basis of approximate entropy, it can effectively analyze the complexity of short sequences. Approximate entropy is a nonlinear parameter identification method that can be used to reflect the complexity and dynamics of time series and measure the irregularity of dynamic series. ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
CPCG16Z99/00
Inventor 李勋贵
Owner LANZHOU UNIVERSITY
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