{"title":"MSE Analysis of 24-Bit Fixed-Point Format in a Wide Variance Range","authors":"B. Denic, Z. Perić, M. Dincic","doi":"10.1109/ICEST58410.2023.10187324","DOIUrl":null,"url":null,"abstract":"In this paper, we consider a fixed-point format which is one of the commonly used binary format for data representation. In particular, we focus on the 24-bit fixed-point format (FXP24) and the analysis provided here can be observed as our further research in this area. Using the relationship that exists between the structure of the fixed-point format and uniform scalar quantization, we actually use SQNR (signal-to-quantization noise ratio) to measure the performance of mentioned binary format. Assuming data modelled with a Laplacian distribution, we theoretically investigate the performance of the FXP24 format across the wide dynamic range of variances under the constraint that the number of bits in the integer part $\\boldsymbol{n}$ changes. We have shown that with an adequate selection of $\\boldsymbol{n}$, it is possible to find the range of variances in which FXP24 provides better SQNR (that is, a higher accuracy) than its floating-point counterpart FP24.","PeriodicalId":278683,"journal":{"name":"2023 58th International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 58th International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEST58410.2023.10187324","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
In this paper, we consider a fixed-point format which is one of the commonly used binary format for data representation. In particular, we focus on the 24-bit fixed-point format (FXP24) and the analysis provided here can be observed as our further research in this area. Using the relationship that exists between the structure of the fixed-point format and uniform scalar quantization, we actually use SQNR (signal-to-quantization noise ratio) to measure the performance of mentioned binary format. Assuming data modelled with a Laplacian distribution, we theoretically investigate the performance of the FXP24 format across the wide dynamic range of variances under the constraint that the number of bits in the integer part $\boldsymbol{n}$ changes. We have shown that with an adequate selection of $\boldsymbol{n}$, it is possible to find the range of variances in which FXP24 provides better SQNR (that is, a higher accuracy) than its floating-point counterpart FP24.