This paper introduces an adaptive filtering process based on shrinking wavelet coefficients from the corresponding signal wavelet representation. The filtering procedure considers a threshold method determined by an iterative algorithm inspired by the control charts application, which is a tool of the statistical process control (SPC). The proposed method, called SpcShrink, is able to discriminate wavelet coefficients that significantly represent the signal of interest. The SpcShrink is algorithmically presented and numerically evaluated according to Monte Carlo simulations. Two empirical applications to real biomedical data filtering are also included and discussed. The SpcShrink shows superior performance when compared with competing algorithms.

翻译：本文提出一种基于信号小波表示中收缩小波系数的自适应滤波过程。该滤波方法采用由控制图应用启发而确定的迭代阈值算法，控制图是统计过程控制（SPC）的一种工具。所提出的方法称为SpcShrink，能够区分显著代表目标信号的小波系数。本文给出了SpcShrink的算法流程，并通过蒙特卡洛模拟进行数值评估。此外，还包含并讨论了两项针对真实生物医学数据滤波的实证应用。与竞争算法相比，SpcShrink展现出更优越的性能。