{"title":"多项式时频分布和时变高阶谱:非平稳信号分析的性能综述","authors":"B. Boashash, B. Ristic","doi":"10.1109/ISSPA.1996.615126","DOIUrl":null,"url":null,"abstract":"A class of Polynomial time-frequency distributions has been recently proposed. It achieves the highest possible concentration in the time-frequency plane for nonlinear polynomial FM signals. Further, it allows to define time-varying higher-order spectra for nonstationary random signals. The paper presents a review of recent results and an application to multi-component signal analysis in the presence of additive and/or multiplicative noise.","PeriodicalId":359344,"journal":{"name":"Fourth International Symposium on Signal Processing and Its Applications","volume":"138 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Polynomial time-frequency distributions and timevarying higher-order spectra: A review of performance for non-stationary signal analysis\",\"authors\":\"B. Boashash, B. Ristic\",\"doi\":\"10.1109/ISSPA.1996.615126\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A class of Polynomial time-frequency distributions has been recently proposed. It achieves the highest possible concentration in the time-frequency plane for nonlinear polynomial FM signals. Further, it allows to define time-varying higher-order spectra for nonstationary random signals. The paper presents a review of recent results and an application to multi-component signal analysis in the presence of additive and/or multiplicative noise.\",\"PeriodicalId\":359344,\"journal\":{\"name\":\"Fourth International Symposium on Signal Processing and Its Applications\",\"volume\":\"138 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Fourth International Symposium on Signal Processing and Its Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSPA.1996.615126\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fourth International Symposium on Signal Processing and Its Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSPA.1996.615126","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Polynomial time-frequency distributions and timevarying higher-order spectra: A review of performance for non-stationary signal analysis
A class of Polynomial time-frequency distributions has been recently proposed. It achieves the highest possible concentration in the time-frequency plane for nonlinear polynomial FM signals. Further, it allows to define time-varying higher-order spectra for nonstationary random signals. The paper presents a review of recent results and an application to multi-component signal analysis in the presence of additive and/or multiplicative noise.
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