摘要
对于非平稳信号,小波多尺度分解是一种有效的信号去噪方法,在D.L.Donoho和I.M.Johnstone提出的多分辨分析小波阈值去噪方法的基础上,采用了一种改进的阈值函数,改进的阈值函数克服了硬阈值函数不连续的缺点,同软阈值函数一样具有连续性,而且解决了软阈值函数中存在的恒定偏差,同时它具有软硬阈值函数不可比拟的灵活性。仿真结果表明,采用了改进的阈值函数的去噪结果有效抑制了在信号奇异点附近产生的Pseudo-Gibbs现象,无论是在视觉效果上,还是在信噪比增益和最小均方误差意义上均优于传统的软硬阈值方法。
It is an effective method to reduce the noises by wavelet much dimension decomposition in non stationary signals. Based on much resolution analysis wavelet threshold de-noising method which put forward by D.L. Donoho and I. M. Johnstone, this paper puts forward an improved de-noising method. This improved threshold function has many advantages over soft threshold function, it overcome the shortcoming of the hard threshold with discontinuous function and solves the problem of the permanent bias in soft threshold function. At the same time, the improved threshold function is more elastic than the soft threshold and hard threshold function. Simulation results indicate that the de-noising method adopting the improved threshold function suppresses the Pseudo-Gibbs phenomena near the singularities of the signal effectively, and the numerical results also show the new method gives better MSE performance and SNR gains than hard threshold and soft threshold methods.
出处
《继电器》
CSCD
北大核心
2007年第18期41-45,49,共6页
Relay
基金
河南省重点科技攻关项目(072102240006)
