{"title":"随机信号最优压缩解压缩的多目标算子","authors":"Pablo Soto-Quiros, A. Torokhti","doi":"10.1109/IWOBI.2018.8464195","DOIUrl":null,"url":null,"abstract":"New multi-objective operators of random signals are presented in this paper. The new operators improve, under a unrestrictive condition, the performance of known techniques: the generalized Karhunen-Loéve transform, the transform considered by Brillinger and the generalized Brillinger-like transform. This is obtained by particular design of new operators which have more parameters to optimize than that of other operators described in literature.","PeriodicalId":127078,"journal":{"name":"2018 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)","volume":"32 ","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-Objective Operator for Optimal Compression and De-compression of Random Signals\",\"authors\":\"Pablo Soto-Quiros, A. Torokhti\",\"doi\":\"10.1109/IWOBI.2018.8464195\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"New multi-objective operators of random signals are presented in this paper. The new operators improve, under a unrestrictive condition, the performance of known techniques: the generalized Karhunen-Loéve transform, the transform considered by Brillinger and the generalized Brillinger-like transform. This is obtained by particular design of new operators which have more parameters to optimize than that of other operators described in literature.\",\"PeriodicalId\":127078,\"journal\":{\"name\":\"2018 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)\",\"volume\":\"32 \",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWOBI.2018.8464195\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWOBI.2018.8464195","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-Objective Operator for Optimal Compression and De-compression of Random Signals
New multi-objective operators of random signals are presented in this paper. The new operators improve, under a unrestrictive condition, the performance of known techniques: the generalized Karhunen-Loéve transform, the transform considered by Brillinger and the generalized Brillinger-like transform. This is obtained by particular design of new operators which have more parameters to optimize than that of other operators described in literature.
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