{"title":"Bussgang和超指数盲反卷积方法的最优性","authors":"G. Scarano, G. Jacovitti","doi":"10.1109/HOST.1997.613524","DOIUrl":null,"url":null,"abstract":"In this contribution, a generalization of the super exponential blind deconvolution method is discussed. The generalization consists in the definition of a \"spikyness\" criterion involving nonlinearities rather than only powers. This allows to rephrase Bussgang deconvolution in the framework of super exponential deconvolution using a spikyness criterion which takes into account the pdf of the input series to be recovered. Improved performance is expected when generalized super exponential deconvolution is tuned to suitable optimality criteria.","PeriodicalId":305928,"journal":{"name":"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"On the optimality of Bussgang and super exponential blind deconvolution methods\",\"authors\":\"G. Scarano, G. Jacovitti\",\"doi\":\"10.1109/HOST.1997.613524\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this contribution, a generalization of the super exponential blind deconvolution method is discussed. The generalization consists in the definition of a \\\"spikyness\\\" criterion involving nonlinearities rather than only powers. This allows to rephrase Bussgang deconvolution in the framework of super exponential deconvolution using a spikyness criterion which takes into account the pdf of the input series to be recovered. Improved performance is expected when generalized super exponential deconvolution is tuned to suitable optimality criteria.\",\"PeriodicalId\":305928,\"journal\":{\"name\":\"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics\",\"volume\":\"66 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-07-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HOST.1997.613524\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HOST.1997.613524","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On the optimality of Bussgang and super exponential blind deconvolution methods
In this contribution, a generalization of the super exponential blind deconvolution method is discussed. The generalization consists in the definition of a "spikyness" criterion involving nonlinearities rather than only powers. This allows to rephrase Bussgang deconvolution in the framework of super exponential deconvolution using a spikyness criterion which takes into account the pdf of the input series to be recovered. Improved performance is expected when generalized super exponential deconvolution is tuned to suitable optimality criteria.
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