{"title":"再生设置中的熵和信道容量及其在马尔可夫信道中的应用","authors":"V. Sharma, S.K. Singh","doi":"10.1109/ISIT.2001.936146","DOIUrl":null,"url":null,"abstract":"We obtain new entropy and mutual information formulae for regenerative stochastic processes. We use them on Markov channels to generalize the results in Goldsmith and Varaiya (1996). Also we obtain tighter bounds on capacity and better algorithms than in Goldsmith and Varaiya.","PeriodicalId":433761,"journal":{"name":"Proceedings. 2001 IEEE International Symposium on Information Theory (IEEE Cat. No.01CH37252)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"112","resultStr":"{\"title\":\"Entropy and channel capacity in the regenerative setup with applications to Markov channels\",\"authors\":\"V. Sharma, S.K. Singh\",\"doi\":\"10.1109/ISIT.2001.936146\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We obtain new entropy and mutual information formulae for regenerative stochastic processes. We use them on Markov channels to generalize the results in Goldsmith and Varaiya (1996). Also we obtain tighter bounds on capacity and better algorithms than in Goldsmith and Varaiya.\",\"PeriodicalId\":433761,\"journal\":{\"name\":\"Proceedings. 2001 IEEE International Symposium on Information Theory (IEEE Cat. No.01CH37252)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-06-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"112\",\"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.2001.936146\",\"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.2001.936146","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Entropy and channel capacity in the regenerative setup with applications to Markov channels
We obtain new entropy and mutual information formulae for regenerative stochastic processes. We use them on Markov channels to generalize the results in Goldsmith and Varaiya (1996). Also we obtain tighter bounds on capacity and better algorithms than in Goldsmith and Varaiya.