{"title":"l2(Zc+)中的非递归小波变换","authors":"Xiaoxin Li, Deyu Qi, Zhengping Qian","doi":"10.1109/PACIIA.2008.45","DOIUrl":null,"url":null,"abstract":"Today, almost all of the implementations of the discrete wavelet transforms are based on the recursive way. However, non-recursive wavelet transforms (NRWT) are more effective and more flexible. We extend the NRWT theory in lscr<sup>2</sup> (Z) and propose a new NRWT theory based on 6 different downsampling modes in lscr<sup>2</sup> (Z<sub>c</sub> <sup>+</sup>). This extending makes NRWT more practical and can be compatible with the traditional recursive wavelet transform. We study the properties of the NRWT under the 6 downsampling modes, W<sub>-3leskles2</sub>, through the analysis of redundancy degree and point out that W<sub>-2</sub> is optimal and the redundancy degrees of W<sub>-2</sub> and W<sub>0</sub> are identical. The analysis of redundancy degree offers a method to choose the NRWT mode.","PeriodicalId":275193,"journal":{"name":"IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application","volume":"162 10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Non-Recursive Wavelet Transforms in l2(Zc+)\",\"authors\":\"Xiaoxin Li, Deyu Qi, Zhengping Qian\",\"doi\":\"10.1109/PACIIA.2008.45\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Today, almost all of the implementations of the discrete wavelet transforms are based on the recursive way. However, non-recursive wavelet transforms (NRWT) are more effective and more flexible. We extend the NRWT theory in lscr<sup>2</sup> (Z) and propose a new NRWT theory based on 6 different downsampling modes in lscr<sup>2</sup> (Z<sub>c</sub> <sup>+</sup>). This extending makes NRWT more practical and can be compatible with the traditional recursive wavelet transform. We study the properties of the NRWT under the 6 downsampling modes, W<sub>-3leskles2</sub>, through the analysis of redundancy degree and point out that W<sub>-2</sub> is optimal and the redundancy degrees of W<sub>-2</sub> and W<sub>0</sub> are identical. The analysis of redundancy degree offers a method to choose the NRWT mode.\",\"PeriodicalId\":275193,\"journal\":{\"name\":\"IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application\",\"volume\":\"162 10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PACIIA.2008.45\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PACIIA.2008.45","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Today, almost all of the implementations of the discrete wavelet transforms are based on the recursive way. However, non-recursive wavelet transforms (NRWT) are more effective and more flexible. We extend the NRWT theory in lscr2 (Z) and propose a new NRWT theory based on 6 different downsampling modes in lscr2 (Zc+). This extending makes NRWT more practical and can be compatible with the traditional recursive wavelet transform. We study the properties of the NRWT under the 6 downsampling modes, W-3leskles2, through the analysis of redundancy degree and point out that W-2 is optimal and the redundancy degrees of W-2 and W0 are identical. The analysis of redundancy degree offers a method to choose the NRWT mode.