{"title":"The indirect rate-distortion function of a binary i.i.d source","authors":"A. Kipnis, S. Rini, A. Goldsmith","doi":"10.1109/ITWF.2015.7360794","DOIUrl":null,"url":null,"abstract":"The indirect source-coding problem in which a Bernoulli process is compressed in a lossy manner from its noisy observations is considered. These noisy observations are obtained by passing the source sequence through a binary symmetric channel so that the channel crossover probability controls the amount of information available about the source realization at the encoder. We use classic results in rate-distortion theory to compute the rate-distortion function for this model as a solution of an exponential equation. In addition, we derive an upper bound on the rate distortion which has a simple closed-form expression and investigate the coding scheme that attains it. These expressions capture precisely the expected behavior of the rate-distortion function: the noisier the source observations, the smaller the reduction in distortion obtained from increasing the compression rate.","PeriodicalId":281890,"journal":{"name":"2015 IEEE Information Theory Workshop - Fall (ITW)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Information Theory Workshop - Fall (ITW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITWF.2015.7360794","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18
Abstract
The indirect source-coding problem in which a Bernoulli process is compressed in a lossy manner from its noisy observations is considered. These noisy observations are obtained by passing the source sequence through a binary symmetric channel so that the channel crossover probability controls the amount of information available about the source realization at the encoder. We use classic results in rate-distortion theory to compute the rate-distortion function for this model as a solution of an exponential equation. In addition, we derive an upper bound on the rate distortion which has a simple closed-form expression and investigate the coding scheme that attains it. These expressions capture precisely the expected behavior of the rate-distortion function: the noisier the source observations, the smaller the reduction in distortion obtained from increasing the compression rate.