Signal's Recovery via Adaptive Gabor Coefficients Shrinking with Bayes Rule

ZHANG Zong-ping; LIU Gui-zhong; ZHANG Zhuo-sheng

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Signal's Recovery via Adaptive Gabor Coefficients Shrinking with Bayes Rule

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- Signal's Recovery via Adaptive Gabor Coefficients Shrinking with Bayes Rule
- Acta Electronica Sinica Vol. 29, Issue 4, Pages: 518-521(2001)
- 作者机构：
  
  西安交通大学信息与通信工程系,西安,710049
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN911.7
- Published：2001
- 稿件说明：
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ZHANG Zong-ping, LIU Gui-zhong, ZHANG Zhuo-sheng. Signal's Recovery via Adaptive Gabor Coefficients Shrinking with Bayes Rule[J]. Acta Electronica Sinica, 2001, 29(4): 518-521.
DOI：

ZHANG Zong-ping, LIU Gui-zhong, ZHANG Zhuo-sheng. Signal's Recovery via Adaptive Gabor Coefficients Shrinking with Bayes Rule[J]. Acta Electronica Sinica, 2001, 29(4): 518-521. DOI：

摘要

信号在联合时频平面内是相对稀疏的

鉴于此

本文通过假设信号Gabor展开系数先验分布和噪声Gabor展开系数的先验分布

然后应用Bayes准则从含噪信号Gabor展开系数的后验分布估计未知信号的Gabor展开系数

实现时变滤波.数值实验表明该方法是合理有效的.

Abstract

Considering the sparseness of Gabor coefficients of the underlying signals in joint time-frequency plane

this paper describes an adaptive signal recovery approach

obtained by shrinking the Gabor coefficients based on Bayes rule.Via the assumption of prior distributions of Gabor coefficients for the unknown signals and noises

we present a closed form expression for the posterior estimation of Gabor coefficients of the unknown signals

implementing time-variable filtering in time-frequency domain.The validity and effectiveness of the proposed scheme are demonstrated with numerical experiments.

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