{"title":"自适应线性预测器的双模结构","authors":"H. Yeh, H. Tu","doi":"10.1109/ISM.2005.23","DOIUrl":null,"url":null,"abstract":"In this paper, we investigate a two-mode structure of adaptive linear predictor with application to speech coding. Initially, this structure has independently adapting low-order cascaded stages that use forward-backward linear prediction algorithm. Later, it switches to a regular transversal structure using least mean square (LMS) algorithm. This method enjoys fast convergence rate at the beginning and accurate tracking of inputs in the steady state.","PeriodicalId":322363,"journal":{"name":"Seventh IEEE International Symposium on Multimedia (ISM'05)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A two-mode structure of adaptive linear predictor\",\"authors\":\"H. Yeh, H. Tu\",\"doi\":\"10.1109/ISM.2005.23\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we investigate a two-mode structure of adaptive linear predictor with application to speech coding. Initially, this structure has independently adapting low-order cascaded stages that use forward-backward linear prediction algorithm. Later, it switches to a regular transversal structure using least mean square (LMS) algorithm. This method enjoys fast convergence rate at the beginning and accurate tracking of inputs in the steady state.\",\"PeriodicalId\":322363,\"journal\":{\"name\":\"Seventh IEEE International Symposium on Multimedia (ISM'05)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Seventh IEEE International Symposium on Multimedia (ISM'05)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISM.2005.23\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Seventh IEEE International Symposium on Multimedia (ISM'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISM.2005.23","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we investigate a two-mode structure of adaptive linear predictor with application to speech coding. Initially, this structure has independently adapting low-order cascaded stages that use forward-backward linear prediction algorithm. Later, it switches to a regular transversal structure using least mean square (LMS) algorithm. This method enjoys fast convergence rate at the beginning and accurate tracking of inputs in the steady state.