Effects of Noise on the Approximate Entropy of Fractional Brownian Motion Sequence
Effects of Noise on the Approximate Entropy of Fractional Brownian Motion Sequence
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DOI：
10.4028/www.scientific.net/amm.444-445.698
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发表时间：
2013-10
期刊：
影响因子：
--
通讯作者：
X. Hu;Li Wan;D. Xie
中科院分区：
文献类型：
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作者：
X. Hu;Li Wan;D. Xie
近似熵是一种广泛使用的衡量系统复杂性或规律性的技术。本文研究了噪声对分数布朗运动近似熵的影响，包括Hurst指数的大小、噪声类型和噪声系数等。结果表明，分数布朗运动的近似熵值随Hurst指数的增大而减小。在分数布朗运动序列中加入白色噪声后，其值有不同程度的增加，并随着数据的增长而趋于稳定。同时，加入泊松噪声后，混合序列的近似熵值发生明显变化，当泊松噪声系数增大时，对近似熵值的影响更大。
Approximate entropy is a widely used technique to measure system complexity or regularity. In this paper, the effects of noise on the approximate entropy of fractional Brownian motion were investigated by some factors including the value of Hurst exponent, different noise type and coefficients. The results show that the values of approximate entropy of fractional Brownian motion decrease with the increase of Hurst exponent. The values increase in different degree after adding white noise in the sequence of fractional Brownian motion, and tend to be stable with the data lengthened. Meanwhile, the values of approximate entropy of mixed sequence change obviously by adding Poisson noise, while multiplying the coefficients of Poisson noise, the effects on the approximate entropy become greater.