Entropy | |
Best Probability Density Function for Random Sampled Data | |
关键词: maximum entropy method; probability density function; Lagrange multipliers; level-function moments; least squares error; adaptive simulated annealing; smoothing noise; | |
DOI : 10.3390/e11041001 | |
来源: mdpi | |
【 摘 要 】
The maximum entropy method is a theoretically sound approach to construct an analytical form for the probability density function (pdf) given a sample of random events. In practice, numerical methods employed to determine the appropriate Lagrange multipliers associated with a set of moments are generally unstable in the presence of noise due to limited sampling. A robust method is presented that always returns the best pdf, where tradeoff in smoothing a highly varying function due to noise can be controlled. An unconventional adaptive simulated annealing technique, called funnel diffusion, determines expansion coefficients for Chebyshev polynomials in the exponential function.
【 授权许可】
CC BY
© 2009 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland.
【 预 览 】
Files | Size | Format | View |
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RO202003190055308ZK.pdf | 1355KB | download |