摘要
鉴于传统的去噪算法中的阈值很难选取到最优值,设计了自适应的阈值选取器,结合最小均方算法和小波阈值去噪算法,提出了一种基于LMS算法的小波去噪方法。该方法根据LMS算法来自适应地控制阈值参数,并实现提升小波阈值去噪。仿真结果表明,该方法优于传统去噪方法,可较大程度地减少信号中的噪声,提高输出信号的信噪比,能很好地提取有用信号的特征。
In view of difficulty to select the optimal threshold value in the traditional de-noising algorithm,a device was designed,which can adaptively select threshold.A novel de-noising method with adaptive threshold value adjustment was proposed,which using LMS algorithm and threshold de-noising method based on wavelet transform.Using LMS algorithm,the method adaptively controled threshold,and made threshold de-noising base on lifting wavelet.The simulation results show that the method is more better than traditional de-noising method.It can greatly reduce the noise of the signal and improve the signal-to-noise ratio of the output signal,and extract characteristics of the useful signal effectivly.
出处
《桂林电子科技大学学报》
2012年第2期150-154,共5页
Journal of Guilin University of Electronic Technology
关键词
提升小波
去噪
自适应
lifting wavelet
de-noising
adaptive
