EMAT回波信号提升小波降噪最佳分解层数研究

Research of optimal decomposition level in denoising the EMAT echo signal based on lifting wavelet

分析了分解层数不同时重构信号间的最小均方误差变化趋势并根据分析结果结合高频系数白化检验自适应确定了最佳的分解层数。讨论了提升小波变换的提升算法以及新的阈值函数,使用了基于提升小波变换的改进阈值函数的方法和选取了一种最优的阈值方法并结合最佳分解层数对电磁超声回波信号进行了去噪处理,验证了算法的有效性。

When the decomposition is different,This article analyzes the reconstruction of signals in the minimum mean square error change tendency and uses the results of the analysis combined with coefficient of high frequency verificationof white noise adaptive confirmed the optimal decomposition level.the article discusses the lifting arithmetic of lifting wavelet transformation and the new threshold function.Then,it uses a new threshold function based on the lifting wavelet transformation and choose a optimization threshold measure and combination of optimal decomposition level in electromagnetism ultrasonic echo signals for signal de-noising.verify the validity of the algorithm.