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shapelet
用于图像的多尺度分析，shapelet变换用matlab 编程实现(shapelet code)
- 2021-04-15 19:48:54下载
- 积分：1
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ab1aa8fbd6fc
一篇关于小波变换和希尔伯特变换的文章，处理的是无功功率。小波变换代码和希尔伯特变化代码(A Wavelet transform and Hilbert transform article, dealing with reactive power.Wavelet transform and Hilbert transform code)
- 2012-04-15 12:50:09下载
- 积分：1
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work
说明： 有小波分解求小波熵，还有小波包技术求解信号特征，适应与分析脑电信号特征(Seeking a wavelet decomposition wavelet entropy, and wavelet packets technique to solve the signal characteristics, and analysis of EEG characteristics of adaptation)
- 2011-03-02 19:53:44下载
- 积分：1
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wavelet
对雾天图像利用小波变换分解，实现图像去雾增强，分解的层数越多，处理后的效果越明显。(On the fog image using wavelet transform decomposition, to achieve the image to fog enhancement, decomposition of the number of layers, the more obvious the effect of the treatment.)
- 2021-04-26 16:28:45下载
- 积分：1
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tuxiangbianh
离散小波变换与离散小波反变换 快速小波变换（Mallat小波分解算法）：对一幅图像做2级小波分解（离散小波变换）与合成（离散小波反变换）(Discrete wavelet transform and discrete wavelet inverse transform fast wavelet transform (Mallat wavelet decomposition): For an image to do 2 wavelet transform (DWT) and synthesis (discrete wavelet inverse transform))
- 2020-12-08 15:39:20下载
- 积分：1
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Wavelet-Shrinkage_-Asymptopia_
小波变换阈值去噪的文章，基于最大最小准则计算(Minimax Estimation, Adaptive Estimation, Nonparametric
Regression, Density Estimation, Spatial Adaptation, Wavelet Orthonormal bases, BesovSpaces, Optimal Recovery.)
- 2016-12-13 21:12:50下载
- 积分：1
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sound_sep1
独立分量分析（ICA）算法编码，盲源信号分离（声音信号的分离）(Independent component analysis (ICA) algorithm coding, Blind Source Separation (voice signal separation))
- 2006-10-31 21:51:31下载
- 积分：1
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waveform275khz
275hz正弦波激励程序，用于模拟波的激发，适用于导波及其他方面，matlab程序(275hz sine wave incentive program for the simulation of wave excitation applied to guide spread to other aspects, matlab program)
- 2012-10-23 10:19:17下载
- 积分：1
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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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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
