Histogram Filter with Smoothing Parameter Setting

A. V. Ausiannikau, V. Kozel
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引用次数: 1

Abstract

A histogram filter with smoothing parameter settings is discussed in the article. The histogram filter can be effectively applied in the problems of identification (recognition) of distribution laws for small amounts of data. The smoothing parameter is determined taking into account the available a priori information regarding the proposed distribution law. The relationship between the mathematical expectations of the chi-square fit criterion of the standard estimation histogram and the use of the histogram filter has been determined. This ratio is determined by the smoothing factor. The numerical value of the smoothing coefficient depends on the following parameters: the amount of data, the number of grouping intervals, and the shape parameters of the distribution law. The paper analyzes the feasibility of using a histogram filter, depending on the ratio of the above parameters. The dependence of the smoothing coefficient on the specified parameters allows one to determine the relationship between the number of data grouping intervals and their volume. The histogram filter is an easy-to-implement tool that can be easily integrated into any open distribution law identification (recognition) algorithm
直方图过滤器平滑参数设置
本文讨论了具有平滑参数设置的直方图滤波器。直方图滤波器可以有效地应用于小数据量分布规律的识别问题。平滑参数的确定考虑了关于所提出的分布规律的可用先验信息。确定了标准估计直方图的卡方拟合准则的数学期望与直方图滤波器的使用之间的关系。这个比率由平滑因子决定。平滑系数的数值取决于以下参数:数据量、分组区间的个数和分布规律的形状参数。本文根据上述参数的比例,分析了使用直方图滤波器的可行性。平滑系数对指定参数的依赖性使人们能够确定数据分组间隔的数量与其体积之间的关系。直方图滤波器是一种易于实现的工具,可以很容易地集成到任何开放分布规律识别(识别)算法中
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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87
审稿时长
8 weeks
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