基于小波多分辨率分析的信号消噪

Wavelet-Based Multiresolution Analysis to Noise Elimination

小波变换是近 10年来迅速发展起来的学科 ,它与傅立叶变换、Gabor变换相比 ,是一个时间和频率的局部变换 ,因而能有效地从信号中提取信息。通过对信号进行多尺度细化分析 ,解决了傅立叶变换不能解决的许多问题。利用噪声信号小波变换的极大值随尺度的加大而显著减少的特点 ,运用小波多分辨率分析进行信号噪声的消除 ,仿真结果表明 :小波多分辨率分析的效果 。

The wavelet transform is a new subject developed quickly in the past ten years Compared with Fourier transform and Gabor transform, the wavelet transform is a part of time-frequency transform, so the message can be obtained from the signals effectively. By means of the fractionized multiresolution analysis to the signals, many problems unalbe to be solved by Fourier tranform have been solved in this way.Based on the fact that the maxima of the noise wavelet transform reduces dramatically with the increase of the scale, we obtain the result that this way is more advanced than the Fourier transform multiresolution analysis to the noise elimination.