Advanced Search
Volume 27 Issue 11
Nov.  2005
Turn off MathJax
Article Contents
Liu Yong-jun, Chen Cai-kou, Wang Zheng-qun . Modified Maximum Scatter-difference Discriminant Analysis and Face Recognition[J]. Journal of Electronics & Information Technology, 2008, 30(1): 190-193. doi: 10.3724/SP.J.1146.2006.00811
Citation: Wang wei-wei, Shui Peng-lang. Wavelet Tramsform Prefilter Design Based on Polynomial Interpolation[J]. Journal of Electronics & Information Technology, 2005, 27(11): 1765-1769.

Wavelet Tramsform Prefilter Design Based on Polynomial Interpolation

  • Received Date: 2004-04-26
  • Rev Recd Date: 2004-12-16
  • Publish Date: 2005-11-19
  • This paper presents a novel method to design prefilters starting from analysis scaling functions and utilizing the algebraic polynomial interpolation. In the case of uniform sampling, the obtained prefilters are time-invariant and its coefficients are linear combinations of the moments of the analysis scaling function. Its approximate order is dependent on the support length of analysis scaling function rather than its degree of regularity. This method provides two outstanding advantages: the prefilters can be designed with higher approximate orders than the existing prefilters, e.g., the special prefilters from the values at integer points of the synthesis scaling function and the prefilters from prescaling function method; moreover, the method is easy to be extended to the case of nonuniform sampling, in which the prefilters are time-variant and their approximate order is dependent on the support length of analysis scaling function as well as the distribution of sample points.
  • Strang G. Wavelets and dilation equations: A brief introduction. SIAM Rev., 1989, 31: 613-627.[2]Sweldens W, Piessens R. Quadrature formulae and asymptotic error expansions for wavelet approximation of smooth functions[J].SIAM J. Numer. Anal.1994, 31(4):1240-1264[3]Unser M. Approximation power of biorthogonal waveletexpansio-[4]ns. IEEE Trans. on Signal Processing, 1996, 44(3): 519-527.[5]Zhang J K. 小波级数变换的初始化及M-带插值小波理论研究. [博士论文], 西安: 西安电子科技大学, 1999.[6]Zhang J K, Bao Z. Initialization of orthogonal discrete wavelet transforms[J].IEEE Trans.on Signal Processing.2000, 48(5):1474-1477[7]Abry P, Flandrin P. On the initialization of the discrete wavelet transform algorithm[J].IEEE Signal Processing Lett.1994, 1(2):32-34[8]Xia X G, Kuo C C J, Zhang Z. Wavelet coefficient computation with optimal prefiltering[J].IEEE Trans.on Signal Processing.1994, 42(8):2191-2197[9]Steffen P, Heller P N, Gopinath R A. Theory of regular M-band wavelet bases[J].IEEE Trans. onSignal Processing.1993, 41(12):3497-3511[10]Burden R L, Faires J D. Numerical Analysis. Brooks/Cole, Thomson Learning, Inc., 1998: 107-166.[11]Cohen A, Daubechies I, Feauveau J C. Biorthogonal bases of compactly supported wavelets[J].Commun. Pure Appl. Math.1992, 45(5):485-560[12]Sweldens W. The lifting scheme: a construction of second generation wavelets[J].SIAM J. Math. Anal.1997, 29(2):511-546
  • Cited by

    Periodical cited type(10)

    1. 暴琳,朱志宇,孙晓燕,徐标. 面向多源异构数据的个性化搜索和推荐算法综述. 控制理论与应用. 2024(02): 189-209 .
    2. 龚桃,杨晓霞,李怡洁. 融合用户活跃度的上下文感知兴趣点推荐算法. 应用科技. 2024(04): 91-99 .
    3. 徐红艳,党依铭,冯勇,王嵘冰. 融合时间信息的序列商品推荐模型. 计算机技术与发展. 2023(03): 139-145 .
    4. 邹小花,邓伦丹. 基于退火算法的软件测试数据侧信道缓存仿真. 计算机仿真. 2023(03): 385-389 .
    5. 叶裴雷,张大斌. 高速运动目标特征关联检测模型仿真. 计算机仿真. 2023(04): 208-212 .
    6. 李胜,刘桂云,何熊熊. 基于类别转移加权张量分解模型的兴趣点分区推荐. 电子与信息学报. 2022(01): 203-210 . 本站查看
    7. 王金威. 基于大数据分析的高校云招聘信息个性化推送研究. 安徽电子信息职业技术学院学报. 2022(04): 25-31 .
    8. 张红霞,董燕辉,肖军弼,杨勇进. 基于行为延迟共享网络的个性化商品推荐方法. 电子与信息学报. 2021(10): 2993-3000 . 本站查看
    9. 李世宝,张益维,刘建航,崔学荣,张玉成. 基于知识图谱共同邻居排序采样的推荐模型. 电子与信息学报. 2021(12): 3522-3529 . 本站查看
    10. 叶继华,杨思渝,左家莉,王明文. 基于时空上下文信息的POI推荐模型研究. 电子与信息学报. 2021(12): 3546-3553 . 本站查看

    Other cited types(12)

  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (2240) PDF downloads(731) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return