摘要
小波理论是一新兴的信号处理理论,它在时间和频率上都有很好的局部性:分析低频信号时,其时间窗很大;分析高频信号时,其时间窗较小。小波理论已成为信号去噪处理中的一种重要的工具。基于传统的阈值去噪方法,在分析研究了它们的优缺点之后,本着改进滤波效果,提高去噪质量的目的,提出了一种改进方法。该改进方法克服了传统阈值去噪方法的缺陷,并适用于进一步的自适应滤波的需求,仿真实验证实了该改进方法的有效性和优越性。
Wavelet theory is a newly boming theory of signal processing and it has good localization in both frequency and time domains: having fine frequency resolution and coarse time resolution at lower frequency;and coarse frequency resolution and fine time resolution at higher frequency.Wavelet theory has played a particularly important role in denoising. After the analysis and study of the classical thresholding denoising methods, this paper presents a new thresholding function based on them,as their modified project,in order to improve the denoising effect.This modified project can overcome the shortcomings Of the classical thresholding denoising methods in some extent,moreover,it can be applied to the adaptive wavelet thresholding denoising algorithm,which is verified through a good many of simulation experiments.
出处
《电脑知识与技术》
2006年第3期154-155,共2页
Computer Knowledge and Technology
关键词
小波理论
阈值去噪
硬阈值
软阈值
wavelet theory
thresholding denoising
hard-thresholding
soft-thresholding