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对图像做二维离散小波变换，分解级数为3级，并重构图像，不直接调用Matlab的dwt和idwt函数。(pair of 2-dimensional images DWT, decomposition of the three series, and Image Reconstruction, not directly call Matlab dwt and idwt function.)

实现小波包的n层分解与重构,以及简单的输入输出方式(Implementation of wavelet packet decomposition and reconstruction of N layer)

MATLAB实现kennard-stone选样本算法 (MATLAB kennard- stone selected sample algorithm)

图像滤波变换程序，上学期课程设计代码，绝对原创(Image filtering transform procedures, last semester curriculum design code, an absolute original)

说明：  提出了一种结合SVD的小波变换方法，对其在外弹道测量数据中的野值剔除进行了研究。对观测数据进行小波分解，将小波分解后的近似分量和细节分量组合实现相空间重构，作为SVD方法的输入观测矩阵，根据奇异 熵增量准则，对奇异值进行筛选，根据SVD逆变换重构原信号。这一方法克服了Hankel矩阵相空间构建方法数据 端点失真问题。以小波分解后分量重构的相空间可以满足正交性，进一步提高了SVD进行数据降噪和野值检测的精度。仿真数据和试验数据处理结果证明了这一方法的有效性。(Proposed a method of combining the SVD wavelet transform its outer ballistic measurement data in excluding outliers were studied. Observational data on wavelet decomposition, wavelet decomposition of the approximate combined component and detail component to achieve the phase space reconstruction, as the input observation matrix SVD method, based on singular entropy increment standards, singular value filter, according to the inverse transform heavy SVD structure of the original signal. This approach overcomes the Hankel matrix phase space construction method data endpoint distortion. Wavelet decomposition component of reconstruction phase space satisfy orthogonality, to further improve the SVD for data noise reduction and outlier detection accuracy. Simulation data and experimental data processing results prove the effectiveness of this approach.)

说明：  实现f-k变换，功能强大，各种滤波处理，地震波等都能用(wavelet transformF -k transform, powerful, a variety of filtering, seismic waves can be used)

小波分析在心电信号去噪中的应用,小波变换在心电图数据处理中的应用研究(Wavelet analysis of ECG signal denoising)

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.)

多种方法（软硬阈值、自适应阈值等）进行小波去噪的matlab程序(A variety of methods (hard and soft threshold, adaptive threshold, etc.) of the matlab wavelet denoising procedures)

离散小波分解，把图像分为高频细节与低频概貌。(Discrete wavelet decomposition, the image is divided into high and low frequency detail overview)