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摘要翻译：
基于移动平均低通滤波器周围的广义高维方差，提出了一种估计高维分形Hurst指数的算法。作为工作实例，我们考虑了由随机中点位移和Cholesky-Levinson因式分解算法生成的粗糙曲面。代理曲面的Hurst指数范围为0.1-0.9，步长为0.1，大小不同。文中还讨论了算法的计算效率和精度。
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英文标题：
《Algorithm to estimate the Hurst exponent of high-dimensional fractals》
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作者：
Anna Carbone
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最新提交年份：
2007
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分类信息：
一级分类：Physics 物理学
二级分类：Statistical Mechanics 统计力学
分类描述：Phase transitions, thermodynamics, field theory, non-equilibrium phenomena, renormalization group and scaling, integrable models, turbulence
相变，热力学，场论，非平衡现象，重整化群和标度，可积模型，湍流
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英文摘要：
We propose an algorithm to estimate the Hurst exponent of high-dimensional fractals, based on a generalized high-dimensional variance around a moving average low-pass filter. As working examples, we consider rough surfaces generated by the Random Midpoint Displacement and by the Cholesky-Levinson Factorization algorithms. The surrogate surfaces have Hurst exponents ranging from 0.1 to 0.9 with step 0.1, and different sizes. The computational efficiency and the accuracy of the algorithm are also discussed.
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PDF链接：
https://arxiv.org/pdf/711.2892
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