{"title":"非平稳信号参数化建模技术及其在低比特率音频编码中的应用","authors":"R. Boyer, S. Essid, N. Moreau","doi":"10.1109/ICOSP.2002.1181082","DOIUrl":null,"url":null,"abstract":"Low bit rate audio coding often relies on Fourier representation despite its limitations for transient signal modeling. This study proposes alternative decompositions and expansion strategies that lead to more accurate modeling. Two classes of methods are considered, subspace decomposition methods, and atomic decomposition methods and their performances are compiled to propose an audio modeling scheme amenable to low bit rate coding.","PeriodicalId":159807,"journal":{"name":"6th International Conference on Signal Processing, 2002.","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Non-stationary signal parametric modeling techniques with an application to low bit rate audio coding\",\"authors\":\"R. Boyer, S. Essid, N. Moreau\",\"doi\":\"10.1109/ICOSP.2002.1181082\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Low bit rate audio coding often relies on Fourier representation despite its limitations for transient signal modeling. This study proposes alternative decompositions and expansion strategies that lead to more accurate modeling. Two classes of methods are considered, subspace decomposition methods, and atomic decomposition methods and their performances are compiled to propose an audio modeling scheme amenable to low bit rate coding.\",\"PeriodicalId\":159807,\"journal\":{\"name\":\"6th International Conference on Signal Processing, 2002.\",\"volume\":\"61 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"6th International Conference on Signal Processing, 2002.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOSP.2002.1181082\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"6th International Conference on Signal Processing, 2002.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOSP.2002.1181082","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Non-stationary signal parametric modeling techniques with an application to low bit rate audio coding
Low bit rate audio coding often relies on Fourier representation despite its limitations for transient signal modeling. This study proposes alternative decompositions and expansion strategies that lead to more accurate modeling. Two classes of methods are considered, subspace decomposition methods, and atomic decomposition methods and their performances are compiled to propose an audio modeling scheme amenable to low bit rate coding.