{"title":"Stochastic quantization transfer functions for high resolution signal estimation","authors":"H. Berndt, H. Jentschel","doi":"10.1109/ICDSP.2002.1028231","DOIUrl":null,"url":null,"abstract":"Scalar signal quantization is commonly based on a deterministic definition of nonlinear transfer functions. However, in the more general case of stochastic quantization a non-deterministic approach is required. This paper presents an analysis of general stochastic quantization properties derived from a model incorporating a regular deterministic quantizer. It is shown how stochastic quantization transfer functions providing constant mean square error independent of the actual probability density distribution of the signal being quantized can be derived. Simulation results illustrating performance and limits of the proposed quantizer are given.","PeriodicalId":351073,"journal":{"name":"2002 14th International Conference on Digital Signal Processing Proceedings. DSP 2002 (Cat. No.02TH8628)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2002 14th International Conference on Digital Signal Processing Proceedings. DSP 2002 (Cat. No.02TH8628)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDSP.2002.1028231","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Scalar signal quantization is commonly based on a deterministic definition of nonlinear transfer functions. However, in the more general case of stochastic quantization a non-deterministic approach is required. This paper presents an analysis of general stochastic quantization properties derived from a model incorporating a regular deterministic quantizer. It is shown how stochastic quantization transfer functions providing constant mean square error independent of the actual probability density distribution of the signal being quantized can be derived. Simulation results illustrating performance and limits of the proposed quantizer are given.