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dt_dwt_A
说明： 双数复数小波变换的Matlab源码的A部分，全部解压到一个文件夹后直接调用函数。(Double the number of complex wavelet transform of the A part of Matlab source code, all extract to a folder call the function directly.)
- 2020-11-06 10:19:50下载
- 积分：1
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xiaobotiqu.m
关于小波包变化的，特征提取的一些程序，可直接运行成功。(Wavelet packet feature extraction)
- 2013-05-07 10:12:56下载
- 积分：1
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harmwave
关于小波分析的程序，用于分析振动信号的程序，很好用(Wavelet analysis on the procedures used to analyze the vibration signal of procedures, very good use)
- 2008-12-17 09:23:29下载
- 积分：1
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CurveLab-2.1.2
curvelet变换最新工具包，含有快速离散曲波变换的所有形式（包括基于usfft和wrapping和3dfdct）。功能强大，是学习曲波变换的好帮手。(curvelet transform the latest kit, containing the fast discrete curvelet transform all forms (including those based on usfft and wrapping and 3dfdct). Powerful learning curvelet transform is a good helper.)
- 2010-09-16 20:55:56下载
- 积分：1
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Daubechies
java小波变换的实现，包括哈尔小波，以及在这基础上改进的小波实现。(The implementation of Daubechies wavelets.)
- 2012-03-27 11:14:14下载
- 积分：1
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zsb
用于折射波处理时的to、θ函数法求界面深度，浅层地震(Used for refraction wave in processing, θ function method to ask interface depth, shallow earthquake)
- 2020-12-20 10:59:10下载
- 积分：1
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EZW_Matlab
对输入的二维灰值图像，先进行提升Haar小波变换，再用经典的EZW算法对小波系数进行压缩，然后反变换重构原图像。(On the importation of two-dimensional gray value of images, first upgrade the Haar wavelet transform, and then classical EZW algorithm to compress the wavelet coefficients, and then inverse transform reconstruction of the original image.)
- 2008-04-09 21:59:48下载
- 积分：1
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GaborandBP
基于Gabor小波变换和人工神经网络的人脸识别方法，matlab代码。(Based on the Gabor wavelet transform and artificial neural network methods for face recognition, matlab code.)
- 2021-05-14 09:30:02下载
- 积分：1
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BE-CO-RO-1991
Fast wavelet transforms and numerical algorithms 1
- 2013-12-27 23:53:23下载
- 积分：1
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BCS-SPL-1.5-new
Block-based random image sampling is coupled with a projectiondriven
compressed-sensing recovery that encourages sparsity in
the domain of directional transforms simultaneously with a smooth
reconstructed image. Both contourlets as well as complex-valued
dual-tree wavelets are considered for their highly directional representation,
while bivariate shrinkage is adapted to their multiscale
decomposition structure to provide the requisite sparsity constraint.
Smoothing is achieved via a Wiener filter incorporated
into iterative projected Landweber compressed-sensing recovery,
yielding fast reconstruction. The proposed approach yields images
with quality that matches or exceeds that produced by a popular,
yet computationally expensive, technique which minimizes total
variation. Additionally, reconstruction quality is substantially
superior to that from several prominent pursuits-based algorithms
that do not include any smoothing
- 2020-11-23 19:29:34下载
- 积分：1
