{"title":"Optimal one-bit quantizers are asymmetric for additive uniform noise","authors":"G. Alirezaei, R. Mathar","doi":"10.1109/ITA.2017.8023459","DOIUrl":null,"url":null,"abstract":"In this paper, we consider one-bit output quantization of an amplitude bounded input-signal subject to arbitrary additive noise. Capacity is then represented in various ways, each demonstrating that finding the optimum quantization threshold q is an extremely difficult problem. For a class of noise distributions, of which a typical representative is the uniform distribution, it is shown that the optimum quantizer is asymmetric. This contradicts intuition, which for symmetric noise expects the optimum threshold to be the average of the input distribution.","PeriodicalId":305510,"journal":{"name":"2017 Information Theory and Applications Workshop (ITA)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Information Theory and Applications Workshop (ITA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITA.2017.8023459","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In this paper, we consider one-bit output quantization of an amplitude bounded input-signal subject to arbitrary additive noise. Capacity is then represented in various ways, each demonstrating that finding the optimum quantization threshold q is an extremely difficult problem. For a class of noise distributions, of which a typical representative is the uniform distribution, it is shown that the optimum quantizer is asymmetric. This contradicts intuition, which for symmetric noise expects the optimum threshold to be the average of the input distribution.