The study of modern methods for extracting and evaluating the informative components of the signal

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Abstract

The method of extreme filtering (EF) is considered, through the use of which signals are decomposed into sign-alternating components. The basis of the method under consideration is signal decomposition based on the removal of known components locally determined by their extreme. The methods of digital signal processing are considered and the results of their application to real data — trends obtained from the paper production scanner are shown. The advantages and disadvantages of the extremefiltration method are analyzed, and the possibility of its use in solving technical problems is shown. The extremefiltering method contains a simple mathematical base that does not require the calculation of transcendental functions, which guarantees higher performance than other methods with comparable results. Keywords empirical mode decomposition (EMD), extreme filtering (EF), singular value decomposition (SSA), spectral analysis, expresses signal analysis, alternating component, informative component
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研究提取和评估信号信息成分的现代方法
考虑了极值滤波(EF)方法,利用极值滤波将信号分解为符号交替分量。所考虑的方法的基础是基于去除由其极值局部确定的已知分量的信号分解。讨论了数字信号处理的方法,并给出了它们在造纸扫描仪实际数据趋势中的应用结果。分析了极值过滤法的优缺点,指出了极值过滤法解决技术问题的可能性。极值滤波方法包含一个简单的数学基础,不需要计算超越函数,这保证了比具有可比结果的其他方法更高的性能。关键词:经验模态分解(EMD)、极值滤波(EF)、奇异值分解(SSA)、频谱分析、表达信号分析、交流分量、信息分量
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