{"title":"作为源编码定理的球覆盖和测度浓度","authors":"Ioannis Kontoyiannis","doi":"10.1109/ISIT.2001.936031","DOIUrl":null,"url":null,"abstract":"We state and solve a general version of the rate-distortion problem. We show that its answer contains, as corollaries: (i) Stein's lemma in hypothesis testing; (ii) Shannon's (1959) lossy source coding theorem; and (iii) new converses to measure-concentration inequalities.","PeriodicalId":433761,"journal":{"name":"Proceedings. 2001 IEEE International Symposium on Information Theory (IEEE Cat. No.01CH37252)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sphere-covering and measure concentration as source coding theorems\",\"authors\":\"Ioannis Kontoyiannis\",\"doi\":\"10.1109/ISIT.2001.936031\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We state and solve a general version of the rate-distortion problem. We show that its answer contains, as corollaries: (i) Stein's lemma in hypothesis testing; (ii) Shannon's (1959) lossy source coding theorem; and (iii) new converses to measure-concentration inequalities.\",\"PeriodicalId\":433761,\"journal\":{\"name\":\"Proceedings. 2001 IEEE International Symposium on Information Theory (IEEE Cat. No.01CH37252)\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-06-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. 2001 IEEE International Symposium on Information Theory (IEEE Cat. No.01CH37252)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISIT.2001.936031\",\"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. 2001 IEEE International Symposium on Information Theory (IEEE Cat. No.01CH37252)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIT.2001.936031","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sphere-covering and measure concentration as source coding theorems
We state and solve a general version of the rate-distortion problem. We show that its answer contains, as corollaries: (i) Stein's lemma in hypothesis testing; (ii) Shannon's (1959) lossy source coding theorem; and (iii) new converses to measure-concentration inequalities.