Locally-adaptive myriad filtration of one-dimensional complex signal

作     者：Tulyakova, Nataliya Neycheva, Tatyana Trofymchuk, Oleksandr Stryzhak, Oleksandr 

作者机构：Institute of Applied Physics The National Academy of Sciences of Ukraine 58 Petropavlivska Str. Sumy40000 Ukraine Department of Analysis and Processing of Biomedical Signals and Data Institute of Biophysics and Biomedical Engineering Bulgarian Academy of Sciences 105 Acad. Georgi Bonchev Str. Sofia1113 Bulgaria Institute of Telecommunications and Global Information Space The National Academy of Sciences of Ukraine Chokolivskiy Bulv. Kyiv186 Ukraine 

出 版 物：《International Journal Bioautomation》 (Int. J. Bioautomotion)

年 卷 期：2018年第22卷第3期

页      面：275-296页

核心收录：

主　　题：Adaptive algorithms 

摘      要：Locally-adaptive algorithms of myriad filtering are proposed with adaptation of a sample myriad linearity parameter K, depending upon local estimates of a signal, and with hard switching of sliding window length settings and a coefficient which influences on the parameter K. Statistical estimates of the filters quality are obtained using a criterion of a minimum mean-square error for a model of one-dimensional complex signal that includes different elementary segments under conditions of additive Gaussian noise with zero mean and different variances and possible spikes presence. Improvement of integral and local performance indicators is shown in comparison to the highly effective non-linear locally-adaptive algorithms for the considered test signal. Having a complex signal of high efficiency, one of the proposed algorithms provides nearly optimal noise suppression at the segments of linear change of a signal;other algorithm provides higher quality of step edge preservation and the best noise suppression on a const signal. Better efficiency in cases of low and high noise levels is achieved by preliminary noise level estimation through comparison of locally-adaptive parameter and thresholds. It is shown that, in order to ensure better spikes removal, it is expedient to pre-process the signal by robust myriad filter with small window length. The considered adaptive nonlinear filters have possibility to be implemented in a real time mode. © 2018 by the authors.