首页 | 本学科首页   官方微博 | 高级检索  
     

多尺度分解下的自适应滤波器组的构建方法
引用本文:朱洪俊,王忠,廖磊,杨玉民. 多尺度分解下的自适应滤波器组的构建方法[J]. 重庆大学学报(自然科学版), 2007, 30(3): 70-73
作者姓名:朱洪俊  王忠  廖磊  杨玉民
作者单位:西南科技大学,制造科学与工程学院,四川,绵阳,621000;西南科技大学,制造科学与工程学院,四川,绵阳,621000;西南科技大学,制造科学与工程学院,四川,绵阳,621000;西南科技大学,制造科学与工程学院,四川,绵阳,621000
摘    要:通过分析自适应滤波和小波变换的多尺度分解滤波的原理与方法,建立了非平稳信号的多尺度分解下自适应滤波器组的构建模型和滤波方法.将小波变换分离出来的噪声成分作为自适应滤波器的输入,通过自适应滤波器组,能实现多种噪声成分的自适应滤波.通过模型验证和工程实例的应用,该方法能实现非平稳信号在同频段对噪声成分和有用信号的最佳估计.通过自适应滤波器组,能同时实现对多种噪声成分的最佳滤波,具有优良的滤波性能.

关 键 词:自适应滤波  小波变换  滤波模型
文章编号:1000-582X(2007)03-0070-04
修稿时间:2006-11-11

Filtering Construct of Adaptive Filter Grou Pwith Multi-scale Decomposition
ZHU Hong-jun,WANG Zhong,LIAO Lei,YANG Yu-ming. Filtering Construct of Adaptive Filter Grou Pwith Multi-scale Decomposition[J]. Journal of Chongqing University(Natural Science Edition), 2007, 30(3): 70-73
Authors:ZHU Hong-jun  WANG Zhong  LIAO Lei  YANG Yu-ming
Affiliation:College of Manufacturing Science and Engineering, Southwest University of Science and Technology, Mianyang 621010, China
Abstract:The principle and method of the adaptive filter and the filtering with wavelet transform were analyzed, and the model and method of adaptive filtering with wavelet transforms for the transient signal was established. The separated noise of signal by the multi-scale decomposition of wavelet transforms, was the input signal of adaptive filter, and accordingly the optimal filtering method of signal-noise decomposition was realized. By the adaptive filter grou Pbased on the wavelet transform, the optimal filtering to the multi-noise of signal is achieved at the same time, and the method presented in this paper has the excellent filtering capability. Examples of application demonstrate that this method presented is excellent to realize the optimal estimate to the valuable signal and noise of the transient signal in the same frequency segment.
Keywords:Adaptive filtering    Wavelet transform    Filter modeling
本文献已被 CNKI 维普 万方数据 等数据库收录!
点击此处可从《重庆大学学报(自然科学版)》浏览原始摘要信息
点击此处可从《重庆大学学报(自然科学版)》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号