{"title":"时变数字信号处理","authors":"N. Huang, J. Aggarwal","doi":"10.1109/CDC.1980.271863","DOIUrl":null,"url":null,"abstract":"The present paper develops a framework for the analysis and synthesis of linear time-varying (LTV) digital filters in the frequency domain. LTV filters are modeled by the successive use of linear time-invariant (LTI) filters. The time-varying digital filtering is also discussed in relation to the notion of the short-time spectrum and the generalized frequency function. In addition, we present an efficient implementation procedure which reduces the number of filter coefficients.","PeriodicalId":332964,"journal":{"name":"1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1980-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Time-varying digital signal processing\",\"authors\":\"N. Huang, J. Aggarwal\",\"doi\":\"10.1109/CDC.1980.271863\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The present paper develops a framework for the analysis and synthesis of linear time-varying (LTV) digital filters in the frequency domain. LTV filters are modeled by the successive use of linear time-invariant (LTI) filters. The time-varying digital filtering is also discussed in relation to the notion of the short-time spectrum and the generalized frequency function. In addition, we present an efficient implementation procedure which reduces the number of filter coefficients.\",\"PeriodicalId\":332964,\"journal\":{\"name\":\"1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1980-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CDC.1980.271863\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.1980.271863","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The present paper develops a framework for the analysis and synthesis of linear time-varying (LTV) digital filters in the frequency domain. LTV filters are modeled by the successive use of linear time-invariant (LTI) filters. The time-varying digital filtering is also discussed in relation to the notion of the short-time spectrum and the generalized frequency function. In addition, we present an efficient implementation procedure which reduces the number of filter coefficients.
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