{"title":"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","authors":"S. Maiz, M. El Badaoui, J. Leskow, C. Servière","doi":"10.1109/WOSSPA.2013.6602375","DOIUrl":null,"url":null,"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.","PeriodicalId":417940,"journal":{"name":"2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Subsampling-based method for testing Cyclostationarity: Application to biomechanical signals\",\"authors\":\"S. Maiz, M. El Badaoui, J. Leskow, C. Servière\",\"doi\":\"10.1109/WOSSPA.2013.6602375\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":417940,\"journal\":{\"name\":\"2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA)\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-05-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WOSSPA.2013.6602375\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WOSSPA.2013.6602375","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Subsampling-based method for testing Cyclostationarity: Application to biomechanical signals
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.