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Wavelet Filtering by Using Nonthreshold Method and Example of Model Doppler Function
Radioelectronics and Communications Systems Pub Date : 2021-09-21 , DOI: 10.3103/s0735272721070049
Yu. K. Taranenko 1 , V. V. Lopatin 2 , O. Yu. Oliynyk 3
Affiliation  

Abstract

The paper is devoted to the comparative analysis of the efficiency of two methods of discrete wavelet filtering. The first method consists in zeroing of the detailing coefficients up to a specific decomposition level, the determination of which was not investigated in the available publications, while the second method is often applied in practice and involves the use of common constrained threshold of detailing coefficients for all the decomposition levels. For finding the level of wavelet decomposition ensuring the minimal filtering error in time domain, the root-mean-square error of model was employed. In this case, the cosine and correlation distances reflect the filter performance efficiency as was revealed on the basis of results of their comparison with Euclidean norms of vectors in frequency domain. The analysis of wavelet filtering efficiency implies the need to divide the plane of noise distribution laws into two areas: one with the laws close to the normal distribution and the second with all the other laws. For the first group of noises with distribution close to normal, the relationship of the filtering error as a function of the decomposition level features a pronounced extreme character (i.e., minimum) making it possible to design simple filters with minimal computational costs by using the minimum error criterion. The comparison of the proposed filtering method with the classical Butterworth filter resulted in obtaining the identical errors with other factors being equal.



中文翻译:

使用非阈值法的小波滤波和模型多普勒函数的例子

摘要

本文致力于对两种离散小波滤波方法的效率进行比较分析。第一种方法包括将详细系数归零到特定分解级别,可用出版物中未研究其确定方法,而第二种方法通常在实践中应用,涉及使用详细系数的通用约束阈值所有的分解层次。为了寻找时域滤波误差最小的小波分解层次,采用模型的均方根误差。在这种情况下,余弦和相关距离反映了滤波器的性能效率,这是基于它们与频域中向量的欧几里德范数的比较结果所揭示的。对小波滤波效率的分析意味着需要将噪声分布规律平面分为两个区域:一个是接近正态分布的规律,另一个是所有其他规律。对于分布接近正态的第一组噪声,作为分解级别函数的滤波误差的关系具有明显的极端特征(即最小值),这使得通过使用最小值来设计具有最小计算成本的简单滤波器成为可能错误准则。所提出的滤波方法与经典巴特沃斯滤波器的比较导致在其他因素相同的情况下获得相同的误差。一个具有接近正态分布的规律,第二个具有所有其他规律。对于分布接近正态的第一组噪声,作为分解级别函数的滤波误差的关系具有明显的极端特征(即最小值),这使得通过使用最小值来设计具有最小计算成本的简单滤波器成为可能错误准则。所提出的滤波方法与经典巴特沃斯滤波器的比较导致在其他因素相同的情况下获得相同的误差。一个具有接近正态分布的规律,第二个具有所有其他规律。对于分布接近正态的第一组噪声,作为分解级别函数的滤波误差的关系具有明显的极端特征(即最小值),这使得通过使用最小值来设计具有最小计算成本的简单滤波器成为可能错误准则。所提出的滤波方法与经典的巴特沃斯滤波器的比较导致在其他因素相同的情况下获得相同的误差。最小)使得通过使用最小误差准则设计具有最小计算成本的简单滤波器成为可能。所提出的滤波方法与经典巴特沃斯滤波器的比较导致在其他因素相同的情况下获得相同的误差。最小)使得通过使用最小误差准则设计具有最小计算成本的简单滤波器成为可能。所提出的滤波方法与经典巴特沃斯滤波器的比较导致在其他因素相同的情况下获得相同的误差。

更新日期:2021-09-22
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