{"title":"最大失真准则的零误差源编码","authors":"E. Tuncel, P. Koulgi, S. Regunathan, K. Rose","doi":"10.1109/DCC.2002.999947","DOIUrl":null,"url":null,"abstract":"Let finite source and reproduction alphabets X and Y and a distortion measure d: X/spl times/Y/spl rarr/[0,/spl infin/) be given. We study the minimum asymptotic rate required to describe a source distributed over X within a (given) distortion threshold D at every sample. The problem is hence a min-max problem, and the distortion measure is extended to vectors as follows: for x/sup n//spl isin/X/sup n/, y/sup n//spl isin/Y/sup n/, d(x/sup n/, y/sup n/)=max/sub i/d(x/sub i/, y/sub i/). In the graph-theoretic formulation we introduce, a code for the problem is a dominating set of an equivalent distortion graph. We introduce a linear programming lower bound for the minimum dominating set size of an arbitrary graph, and show that this bound is also the minimum asymptotic rate required for the corresponding source. Turning then to the optimality of scalar coding, we show that scalar codes are asymptotically optimal if the underlying graph is either an interval graph or a tree.","PeriodicalId":420897,"journal":{"name":"Proceedings DCC 2002. Data Compression Conference","volume":"449 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Zero-error source coding with maximum distortion criterion\",\"authors\":\"E. Tuncel, P. Koulgi, S. Regunathan, K. Rose\",\"doi\":\"10.1109/DCC.2002.999947\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Let finite source and reproduction alphabets X and Y and a distortion measure d: X/spl times/Y/spl rarr/[0,/spl infin/) be given. We study the minimum asymptotic rate required to describe a source distributed over X within a (given) distortion threshold D at every sample. The problem is hence a min-max problem, and the distortion measure is extended to vectors as follows: for x/sup n//spl isin/X/sup n/, y/sup n//spl isin/Y/sup n/, d(x/sup n/, y/sup n/)=max/sub i/d(x/sub i/, y/sub i/). In the graph-theoretic formulation we introduce, a code for the problem is a dominating set of an equivalent distortion graph. We introduce a linear programming lower bound for the minimum dominating set size of an arbitrary graph, and show that this bound is also the minimum asymptotic rate required for the corresponding source. Turning then to the optimality of scalar coding, we show that scalar codes are asymptotically optimal if the underlying graph is either an interval graph or a tree.\",\"PeriodicalId\":420897,\"journal\":{\"name\":\"Proceedings DCC 2002. Data Compression Conference\",\"volume\":\"449 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-04-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings DCC 2002. Data Compression Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DCC.2002.999947\",\"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 DCC 2002. Data Compression Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DCC.2002.999947","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Zero-error source coding with maximum distortion criterion
Let finite source and reproduction alphabets X and Y and a distortion measure d: X/spl times/Y/spl rarr/[0,/spl infin/) be given. We study the minimum asymptotic rate required to describe a source distributed over X within a (given) distortion threshold D at every sample. The problem is hence a min-max problem, and the distortion measure is extended to vectors as follows: for x/sup n//spl isin/X/sup n/, y/sup n//spl isin/Y/sup n/, d(x/sup n/, y/sup n/)=max/sub i/d(x/sub i/, y/sub i/). In the graph-theoretic formulation we introduce, a code for the problem is a dominating set of an equivalent distortion graph. We introduce a linear programming lower bound for the minimum dominating set size of an arbitrary graph, and show that this bound is also the minimum asymptotic rate required for the corresponding source. Turning then to the optimality of scalar coding, we show that scalar codes are asymptotically optimal if the underlying graph is either an interval graph or a tree.