{"title":"具有马尔可夫性的高斯多终端信源编码:一个有效可计算的外界","authors":"O. Bilgen, A. Wagner","doi":"10.1109/ISIT44484.2020.9174414","DOIUrl":null,"url":null,"abstract":"We provide a method for outer bounding the rate- distortion region of Gaussian distributed compression problems in which the source variables can be embedded in a Gauss- Markov tree. The outer bound so obtained takes the form of a convex optimization problem. Simulations demonstrate that the outer bound is close to the Berger-Tung inner bound, coinciding with it in many cases.","PeriodicalId":159311,"journal":{"name":"2020 IEEE International Symposium on Information Theory (ISIT)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Gaussian Multiterminal Source-Coding with Markovity: An Efficiently-Computable Outer Bound\",\"authors\":\"O. Bilgen, A. Wagner\",\"doi\":\"10.1109/ISIT44484.2020.9174414\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We provide a method for outer bounding the rate- distortion region of Gaussian distributed compression problems in which the source variables can be embedded in a Gauss- Markov tree. The outer bound so obtained takes the form of a convex optimization problem. Simulations demonstrate that the outer bound is close to the Berger-Tung inner bound, coinciding with it in many cases.\",\"PeriodicalId\":159311,\"journal\":{\"name\":\"2020 IEEE International Symposium on Information Theory (ISIT)\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Symposium on Information Theory (ISIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISIT44484.2020.9174414\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Symposium on Information Theory (ISIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIT44484.2020.9174414","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Gaussian Multiterminal Source-Coding with Markovity: An Efficiently-Computable Outer Bound
We provide a method for outer bounding the rate- distortion region of Gaussian distributed compression problems in which the source variables can be embedded in a Gauss- Markov tree. The outer bound so obtained takes the form of a convex optimization problem. Simulations demonstrate that the outer bound is close to the Berger-Tung inner bound, coinciding with it in many cases.
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