{"title":"利用多尺度小波表示对信号进行多阶段分类","authors":"Urszula Libal","doi":"10.1109/MMAR.2010.5587246","DOIUrl":null,"url":null,"abstract":"The aim of signal decomposition in wavelet bases is to represent a signal as a sequence of wavelet coefficients sets. There is proposed a multistage classification rule using on every stage only one set of the signal coefficients. The hierarchical construction of wavelet multiresolution analysis was an inspiration for the multistage classification rule. The algorithm makes an optimal decision for every set of coefficients and its main advantage is a smaller dimension of classification problem on every stage.","PeriodicalId":336219,"journal":{"name":"2010 15th International Conference on Methods and Models in Automation and Robotics","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Multistage classification of signals with the use of multiscale wavelet representation\",\"authors\":\"Urszula Libal\",\"doi\":\"10.1109/MMAR.2010.5587246\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The aim of signal decomposition in wavelet bases is to represent a signal as a sequence of wavelet coefficients sets. There is proposed a multistage classification rule using on every stage only one set of the signal coefficients. The hierarchical construction of wavelet multiresolution analysis was an inspiration for the multistage classification rule. The algorithm makes an optimal decision for every set of coefficients and its main advantage is a smaller dimension of classification problem on every stage.\",\"PeriodicalId\":336219,\"journal\":{\"name\":\"2010 15th International Conference on Methods and Models in Automation and Robotics\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-09-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 15th International Conference on Methods and Models in Automation and Robotics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MMAR.2010.5587246\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 15th International Conference on Methods and Models in Automation and Robotics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMAR.2010.5587246","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multistage classification of signals with the use of multiscale wavelet representation
The aim of signal decomposition in wavelet bases is to represent a signal as a sequence of wavelet coefficients sets. There is proposed a multistage classification rule using on every stage only one set of the signal coefficients. The hierarchical construction of wavelet multiresolution analysis was an inspiration for the multistage classification rule. The algorithm makes an optimal decision for every set of coefficients and its main advantage is a smaller dimension of classification problem on every stage.
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