{"title":"删除信道的平均情形重构:次多项式多道就足够了","authors":"Y. Peres, Alex Zhai","doi":"10.1109/FOCS.2017.29","DOIUrl":null,"url":null,"abstract":"The deletion channel takes as input a bit string x ∊ {0,1}^n, and deletes each bit independently with probability q, yielding a shorter string. The trace reconstruction problem is to recover an unknown string x ∊ from many independent outputs (called traces) of the deletion channel applied to x.We show that if x is drawn uniformly at random and q","PeriodicalId":311592,"journal":{"name":"2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"52","resultStr":"{\"title\":\"Average-Case Reconstruction for the Deletion Channel: Subpolynomially Many Traces Suffice\",\"authors\":\"Y. Peres, Alex Zhai\",\"doi\":\"10.1109/FOCS.2017.29\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The deletion channel takes as input a bit string x ∊ {0,1}^n, and deletes each bit independently with probability q, yielding a shorter string. The trace reconstruction problem is to recover an unknown string x ∊ from many independent outputs (called traces) of the deletion channel applied to x.We show that if x is drawn uniformly at random and q\",\"PeriodicalId\":311592,\"journal\":{\"name\":\"2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"52\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FOCS.2017.29\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FOCS.2017.29","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Average-Case Reconstruction for the Deletion Channel: Subpolynomially Many Traces Suffice
The deletion channel takes as input a bit string x ∊ {0,1}^n, and deletes each bit independently with probability q, yielding a shorter string. The trace reconstruction problem is to recover an unknown string x ∊ from many independent outputs (called traces) of the deletion channel applied to x.We show that if x is drawn uniformly at random and q