Subsampling-based method for testing Cyclostationarity: Application to biomechanical signals

S. Maiz, M. El Badaoui, J. Leskow, C. Servière
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引用次数: 5

Abstract

In last decades, a well-studied characteristic of signals called Cyclostationarity (CS) has provided very important survey, highlighting the impact of CS models on signal analysis in telecommunication, mechanical, acoustic, biomechanical and econometric signals. It is a technique that offers diagnostic advantages for the analysis of failures, faults and disturbances which are related to a system being examined. The aim of this paper is to introduce the concept of CS for signals and to present possibilities of statistical resampling procedures available for such signals. The resampling method treated in this paper is referred to as Subsampling. A description of this method is presented and its applicability to CS simulated and real data is proved. This implies, in particular, that statistical CS analysis can be carried out without the assumption of Gaussianity on the CS process under consideration.
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基于次抽样的循环平稳性测试方法:在生物力学信号中的应用
在过去的几十年里,一个被充分研究的信号特征——循环平稳性(CS)提供了非常重要的调查,突出了CS模型在电信、机械、声学、生物力学和计量经济学信号分析中的影响。这是一种为分析与被检查系统有关的故障、故障和干扰提供诊断优势的技术。本文的目的是介绍信号的CS概念,并提出可用于此类信号的统计重采样程序的可能性。本文处理的重采样方法称为次采样。给出了该方法的描述,并证明了该方法对CS仿真数据和实际数据的适用性。这特别意味着,统计CS分析可以在不假设所考虑的CS过程的高斯性的情况下进行。
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