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li5-39
先进行提升小波变换，然后使用提升小波进行图像的分解和重构(Be carried out on lifting wavelet transform, and then use the images to enhance the wavelet decomposition and reconstruction)
- 2020-07-20 11:58:47下载
- 积分：1
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Daubechies4-Hilbert
实现信号希尔伯特变换，以及小波变换，小波变换要求数据长度是2的N次幂(The signal Hilbert transform and wavelet transform, wavelet transform requires that the data length 2 is N th)
- 2013-05-18 23:42:25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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KS-sampling
MATLAB实现kennard-stone选样本算法
(MATLAB kennard- stone selected sample algorithm)
- 2021-01-19 22:18:41下载
- 积分：1
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raj
this is mat lab wavelet paper
- 2009-10-27 13:45:04下载
- 积分：1
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GaborFilter
说明： 利用Gabor滤波器提取图像纹理特征，用于图像分类模式识别(Extract the texture feature using Gabor filter/wavelet. You should first generate cell array G, which is a set of kernels in freq domain, then pass G and the image to the function GABORCONV.)
- 2011-04-10 15:58:05下载
- 积分：1
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wavelet
小波变换，反变换，以及提升小波变换，包括97小波，及53小波(Wavelet transform, inverse transform, as well as the lifting wavelet transform, including the 97 wavelet, and 53 wavelet)
- 2021-01-06 11:58:55下载
- 积分：1
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RECGGdenoisiie
去除在心电信号采集过程中混入的肌电干扰、工频干扰、基线漂移等噪声信信号，避免噪声对心电信号特征点的识别与提取造成误判漏判 已通过测试。
(Remove the EMG interference mixed with the signal acquisition process in mind, frequency interference, baseline drift and noise channel signal to avoid noise caused by the misjudgment of the Missing has been tested on ECG feature identification and extraction.)
- 2012-08-13 08:45:17下载
- 积分：1
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wave-move
描述电磁波（电场或磁场）在自由空间传播的Matlab程序。(Description of electromagnetic waves (electric or magnetic) in free-space propagation of Matlab procedures.)
- 2020-11-03 09:39:52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
