{"title":"二次时频分布:新的双曲类及其与仿射类的交集","authors":"A. Papandreou, F. Hlawatsch, G. Boudreaux-Bartels","doi":"10.1109/SSAP.1992.246840","DOIUrl":null,"url":null,"abstract":"The proposed new class of quadratic time-frequency distributions is based on the 'hyperbolic time shift' and scale invariance properties that are important in the analysis of Doppler invariant signals used in bat and dolphin echolocation, and of 'locally self-similar' signals used in fractals and fractional Brownian motion. The hyperbolic class can be characterized by 2-D kernels, and kernel constraints are derived for some desirable TFD properties. The Bertrand distribution and the Altes distribution are members of the hyperbolic class. The authors define a 'localized' subclass and study the intersection between the affine class and the hyperbolic class.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Quadratic time-frequency distributions: the new hyperbolic class and its intersection with the affine class\",\"authors\":\"A. Papandreou, F. Hlawatsch, G. Boudreaux-Bartels\",\"doi\":\"10.1109/SSAP.1992.246840\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The proposed new class of quadratic time-frequency distributions is based on the 'hyperbolic time shift' and scale invariance properties that are important in the analysis of Doppler invariant signals used in bat and dolphin echolocation, and of 'locally self-similar' signals used in fractals and fractional Brownian motion. The hyperbolic class can be characterized by 2-D kernels, and kernel constraints are derived for some desirable TFD properties. The Bertrand distribution and the Altes distribution are members of the hyperbolic class. The authors define a 'localized' subclass and study the intersection between the affine class and the hyperbolic class.<<ETX>>\",\"PeriodicalId\":309407,\"journal\":{\"name\":\"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-10-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SSAP.1992.246840\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSAP.1992.246840","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Quadratic time-frequency distributions: the new hyperbolic class and its intersection with the affine class
The proposed new class of quadratic time-frequency distributions is based on the 'hyperbolic time shift' and scale invariance properties that are important in the analysis of Doppler invariant signals used in bat and dolphin echolocation, and of 'locally self-similar' signals used in fractals and fractional Brownian motion. The hyperbolic class can be characterized by 2-D kernels, and kernel constraints are derived for some desirable TFD properties. The Bertrand distribution and the Altes distribution are members of the hyperbolic class. The authors define a 'localized' subclass and study the intersection between the affine class and the hyperbolic class.<>