Waveform Estimation of Non-Stationary Fractal Stochastic Signals Using Optimum Threshold Technique

ZHANG Ke-shu; MA Hong; YOU Zhi-sheng; Michio Umeda

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Waveform Estimation of Non-Stationary Fractal Stochastic Signals Using Optimum Threshold Technique

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- Waveform Estimation of Non-Stationary Fractal Stochastic Signals Using Optimum Threshold Technique
- Acta Electronica Sinica Vol. 29, Issue 9, Pages: 1161-1163(2001)
- 作者机构：
  
  1. 四川大学数学学院,四川,成都,610064
  2. 四川大学计算机学院,四川,成都,610064
  3. 大阪电气通信大学情报工学部,日本大阪府寝屋川市
  4. 四川大学数学学院四川成都,610064
  5. 四川大学计算机学院四川成都,610064
  6. 大阪电气通信大学情报工学部日本大阪府寝屋川市
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN911.7
- Published：2001
- 稿件说明：
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ZHANG Ke-shu, MA Hong, YOU Zhi-sheng, et al. Waveform Estimation of Non-Stationary Fractal Stochastic Signals Using Optimum Threshold Technique[J]. Acta Electronica Sinica, 2001, 29(9): 1161-1163.
DOI：

ZHANG Ke-shu, MA Hong, YOU Zhi-sheng, et al. Waveform Estimation of Non-Stationary Fractal Stochastic Signals Using Optimum Threshold Technique[J]. Acta Electronica Sinica, 2001, 29(9): 1161-1163. DOI：

摘要

本文用基于最小均方误差准则的最优门限方法估计叠加高斯白噪声的分形布朗运动

并给出其离散小波变换分解级数确定方法.与多尺度维纳滤波相比

本方法不需估计1/f类分形信号的方差

且其离散小波变换分解级数可预先确定

因此有着更好的实用性和可操作性.

Abstract

Based on the minimum mean-square error

this paper offers an optimum threshold method of estimating the 1/f-type fractal signals with the additive white noise.The paper also provides the method of determining the wavelet decomposition scale.Compared with the multiscale Wiener filter

the optimum threshold method is more practical and maneuverable because it doesn't estimate the variance of 1/f-type fractal signals and the wavelet decomposition scale can be determined in advance.

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