{"title":"一个乘法Zac变换","authors":"R. Tolimieri","doi":"10.1109/MDSP.1989.97061","DOIUrl":null,"url":null,"abstract":"Summary form only given. A multiplicative Zac transform that plays the same role in analyzing affine group wavelets as the standard Zac transform plays in Heisenberg-Weyl wavelet theory has been defined in frequency space for causal signals. This construction is based on dilated complex exponentials that are eigenvectors of a sequence of dilation operators. Algorithms, based on the finite Fourier transform have been designed for analysis and synthesis of signals passing through the multiplicative Zac transform.<<ETX>>","PeriodicalId":340681,"journal":{"name":"Sixth Multidimensional Signal Processing Workshop,","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1989-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A multiplicative Zac transform\",\"authors\":\"R. Tolimieri\",\"doi\":\"10.1109/MDSP.1989.97061\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Summary form only given. A multiplicative Zac transform that plays the same role in analyzing affine group wavelets as the standard Zac transform plays in Heisenberg-Weyl wavelet theory has been defined in frequency space for causal signals. This construction is based on dilated complex exponentials that are eigenvectors of a sequence of dilation operators. Algorithms, based on the finite Fourier transform have been designed for analysis and synthesis of signals passing through the multiplicative Zac transform.<<ETX>>\",\"PeriodicalId\":340681,\"journal\":{\"name\":\"Sixth Multidimensional Signal Processing Workshop,\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1989-09-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sixth Multidimensional Signal Processing Workshop,\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MDSP.1989.97061\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sixth Multidimensional Signal Processing Workshop,","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MDSP.1989.97061","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Summary form only given. A multiplicative Zac transform that plays the same role in analyzing affine group wavelets as the standard Zac transform plays in Heisenberg-Weyl wavelet theory has been defined in frequency space for causal signals. This construction is based on dilated complex exponentials that are eigenvectors of a sequence of dilation operators. Algorithms, based on the finite Fourier transform have been designed for analysis and synthesis of signals passing through the multiplicative Zac transform.<>
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