An Adaptive Filter Model Based on Wavelet Transform

被引：1

作者：

Wang Jianhui ^{[1
]}

Xiao Qian ^{[1
]}

Jiang Yan ^{[1
]}

Guan Shouping ^{[1
]}

Gu Shusheng ^{[1
]}

机构：

[1] Northeastern Univ, Minist Educ, Key Lab Proc Ind Automat, Shenyang, Peoples R China

来源：

PROCEEDINGS OF THE 2009 WRI GLOBAL CONGRESS ON INTELLIGENT SYSTEMS, VOL III | 2009年

关键词：

Wavelet transform; Denoising; Adaptive Filtering; Weight;

D O I：

10.1109/GCIS.2009.342

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Due to the fact that it is not easy to filter out the overlap noise between noisy signal and noise using the traditional method of wavelet denoising, an adaptive filter model based on the wavelet transform is constructed. In this model, the adaptive filter is used to filter out noise secondary on the basis of first wavelet denoising on the original noisy signal. The experimental results show that the model can effectively remove the noise. And comparing with the original method of wavelet denosing, the SNR of the signal which uses the model to filter out noise is much higher, reaching a better filtering effect.

引用

页码：136 / 139

页数：4

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