{"title":"Properties of optimal prefix-free machines as instantaneous codes","authors":"K. Tadaki","doi":"10.1109/CIG.2010.5592776","DOIUrl":null,"url":null,"abstract":"The optimal prefix-free machine U is a universal decoding algorithm used to define the notion of program-size complexity H(s) for a finite binary string s. Since the set of all halting inputs for U is chosen to form a prefix-free set, the optimal prefix-free machine can be regarded as an instantaneous code for noiseless source coding scheme. In this paper, we investigate the properties of optimal prefix-free machines as instantaneous codes. In particular, we investigate the properties of the set U−1(s) of codewords associated with a symbol s. Namely, we investigate the number of codewords in U−1(s) and the distribution of codewords in U−1(s) for each symbol s, using the toolkit of algorithmic information theory.","PeriodicalId":354925,"journal":{"name":"2010 IEEE Information Theory Workshop","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE Information Theory Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIG.2010.5592776","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The optimal prefix-free machine U is a universal decoding algorithm used to define the notion of program-size complexity H(s) for a finite binary string s. Since the set of all halting inputs for U is chosen to form a prefix-free set, the optimal prefix-free machine can be regarded as an instantaneous code for noiseless source coding scheme. In this paper, we investigate the properties of optimal prefix-free machines as instantaneous codes. In particular, we investigate the properties of the set U−1(s) of codewords associated with a symbol s. Namely, we investigate the number of codewords in U−1(s) and the distribution of codewords in U−1(s) for each symbol s, using the toolkit of algorithmic information theory.