{"title":"具有最大似然解码的稳健标量量化的盒中青蛙索引码","authors":"Ilju Na, D. Neuhoff","doi":"10.1109/ISIT.2004.1365464","DOIUrl":null,"url":null,"abstract":"The performance of frog-in-the box (FIB) code index assignments is numerically investigated when maximum likelihood (ML) decoding is used in place of optimal MMSE decoding. Specifically, the reproduction levels are chosen to be those that would be used for a noiseless channel, and the decoder simply maps the channel output to a level whose index codeword is closest to the channel output.","PeriodicalId":269907,"journal":{"name":"International Symposium onInformation Theory, 2004. ISIT 2004. Proceedings.","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2004-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Frog-in-the-box index codes with maximum likelihood decoding for robust scalar quantization\",\"authors\":\"Ilju Na, D. Neuhoff\",\"doi\":\"10.1109/ISIT.2004.1365464\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The performance of frog-in-the box (FIB) code index assignments is numerically investigated when maximum likelihood (ML) decoding is used in place of optimal MMSE decoding. Specifically, the reproduction levels are chosen to be those that would be used for a noiseless channel, and the decoder simply maps the channel output to a level whose index codeword is closest to the channel output.\",\"PeriodicalId\":269907,\"journal\":{\"name\":\"International Symposium onInformation Theory, 2004. ISIT 2004. Proceedings.\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Symposium onInformation Theory, 2004. ISIT 2004. Proceedings.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISIT.2004.1365464\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Symposium onInformation Theory, 2004. ISIT 2004. Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIT.2004.1365464","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Frog-in-the-box index codes with maximum likelihood decoding for robust scalar quantization
The performance of frog-in-the box (FIB) code index assignments is numerically investigated when maximum likelihood (ML) decoding is used in place of optimal MMSE decoding. Specifically, the reproduction levels are chosen to be those that would be used for a noiseless channel, and the decoder simply maps the channel output to a level whose index codeword is closest to the channel output.
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