Wavelet-analysis

使用傅里叶变换和小波变换提取心电信号中的呼吸信号(Using the Fourier transform and the wavelet transform to extract the breathing signal ECG)

多点目标 单站SAR的回波信号仿真以及BP后向投影成像 参数见合成孔径雷达成像——算法与实现一书表6.1 运行结果正确，注释比较详细(Percent more single station SAR point target echo signal simulation and backward projection imaging BP parameters, see synthetic aperture radar imaging- algorithm and implementation of a book Table 6.1 run result is correct, more detailed notes)

利用小波变换实现和直方图均衡化相对比的图像的增强与分割.应该比较有用.分割也采取了几种技术的对比(using wavelet transform and histogram equalization relative ratio of image enhancement and segmentation. Be more useful. Pm cutting has taken several technical contrast)

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.)

基于matlab 的图像小波变换，加噪，去噪，增强，重构去噪图像(Based on the matlab image wavelet transform, added a noise, denoising, enhancing, reconstruction image denoising)

基于四阶累积量的矩阵方程法子波估计,对研究子波的有一定的帮助(based on the forth cumulantion seismic wavelet estimation)

小波分解在图像处理和电能质量分析中应用广泛，本文应用小波分解的方法将高频的暂态信号提取出来，获取暂态信号的特征量，就能够有效地计算暂态信号。(Wavelet decomposition in image processing and power quality analysis is widely used, this application of wavelet decomposition method to extract high-frequency transient signals, to obtain the amount of transient characteristics of the signal, we can effectively calculate the transient signal.)

形态成分析（MCA）用于图像分割与去噪的实验代码(Form into analysis (MCA) for image segmentation and denoising experimental code)

说明：  可以将目标矩阵进行线性褶积运算，用于数字信号处理(The target matrix can be linearly convoluted for digital signal processing)

说明：  GHM多小波的变换与逆变换，包括预处理和后处理(GHM multi-wavelet transform and inverse transform)