{"title":"多速率线性系统中的周期平稳信号","authors":"R. Dhuli, Brejesh Lall","doi":"10.1109/NCC.2010.5430197","DOIUrl":null,"url":null,"abstract":"This paper presents a systematic approach to use time frequency representation (TFR) for the analysis of cyclostationary signals in multirate linear systems. We exploit the ability of blocking operation to perform the analysis in a simple yet efficient manner. We illustrate the strength of TFR for performing such analysis. The basic idea is — TFR of a cyclostationary signal is directly related to the rows of the power spectrum matrix of its blocked version. We present examples including nonuniform filter bank to highlight the capabilities of the analysis.","PeriodicalId":130953,"journal":{"name":"2010 National Conference On Communications (NCC)","volume":"06 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Cyclostationary signals in multirate linear systems\",\"authors\":\"R. Dhuli, Brejesh Lall\",\"doi\":\"10.1109/NCC.2010.5430197\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a systematic approach to use time frequency representation (TFR) for the analysis of cyclostationary signals in multirate linear systems. We exploit the ability of blocking operation to perform the analysis in a simple yet efficient manner. We illustrate the strength of TFR for performing such analysis. The basic idea is — TFR of a cyclostationary signal is directly related to the rows of the power spectrum matrix of its blocked version. We present examples including nonuniform filter bank to highlight the capabilities of the analysis.\",\"PeriodicalId\":130953,\"journal\":{\"name\":\"2010 National Conference On Communications (NCC)\",\"volume\":\"06 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-03-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 National Conference On Communications (NCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NCC.2010.5430197\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 National Conference On Communications (NCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NCC.2010.5430197","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cyclostationary signals in multirate linear systems
This paper presents a systematic approach to use time frequency representation (TFR) for the analysis of cyclostationary signals in multirate linear systems. We exploit the ability of blocking operation to perform the analysis in a simple yet efficient manner. We illustrate the strength of TFR for performing such analysis. The basic idea is — TFR of a cyclostationary signal is directly related to the rows of the power spectrum matrix of its blocked version. We present examples including nonuniform filter bank to highlight the capabilities of the analysis.