{"title":"用估计小波变换逼近数字信号","authors":"A. Yajnik","doi":"10.1109/ICCSA.2011.49","DOIUrl":null,"url":null,"abstract":"This article presents a general outline of the approximation of digital signal using Discrete Wavelet. The technique used in [1] is a new attitude to a multi resolution digital signal analysis by discrete wavelet transforms. This article demonstrates an approximation of a digital signal using Daubechies D4 wavelets. The present technique exhibits a revised procedure of removing distortion (loss) generated from the approximated double length digital signal presented in [1]. For highly nonlinear digital signal the technique of [1] fails to approximate the signal but the proposed revised technique can approximate the signal. The proposed method not only enables approximating digital signals in a better way but also it can approximate highly nonlinear digital signals. Moreover, the energy conservation is exactly double than the original signal which is not achieved by the approximation technique discussed in [1].","PeriodicalId":428638,"journal":{"name":"2011 International Conference on Computational Science and Its Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Approximation of a Digital Signal Using Estimate Wavelet Transform\",\"authors\":\"A. Yajnik\",\"doi\":\"10.1109/ICCSA.2011.49\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article presents a general outline of the approximation of digital signal using Discrete Wavelet. The technique used in [1] is a new attitude to a multi resolution digital signal analysis by discrete wavelet transforms. This article demonstrates an approximation of a digital signal using Daubechies D4 wavelets. The present technique exhibits a revised procedure of removing distortion (loss) generated from the approximated double length digital signal presented in [1]. For highly nonlinear digital signal the technique of [1] fails to approximate the signal but the proposed revised technique can approximate the signal. The proposed method not only enables approximating digital signals in a better way but also it can approximate highly nonlinear digital signals. Moreover, the energy conservation is exactly double than the original signal which is not achieved by the approximation technique discussed in [1].\",\"PeriodicalId\":428638,\"journal\":{\"name\":\"2011 International Conference on Computational Science and Its Applications\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-06-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Computational Science and Its Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSA.2011.49\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Computational Science and Its Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSA.2011.49","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Approximation of a Digital Signal Using Estimate Wavelet Transform
This article presents a general outline of the approximation of digital signal using Discrete Wavelet. The technique used in [1] is a new attitude to a multi resolution digital signal analysis by discrete wavelet transforms. This article demonstrates an approximation of a digital signal using Daubechies D4 wavelets. The present technique exhibits a revised procedure of removing distortion (loss) generated from the approximated double length digital signal presented in [1]. For highly nonlinear digital signal the technique of [1] fails to approximate the signal but the proposed revised technique can approximate the signal. The proposed method not only enables approximating digital signals in a better way but also it can approximate highly nonlinear digital signals. Moreover, the energy conservation is exactly double than the original signal which is not achieved by the approximation technique discussed in [1].