CurveLab1.0

利用小波变换检测回波,经过labview显示，实现了很好的界面效果(Using wavelet transform to detect echoes through labview display interface to achieve a good effect)

波的合成及拍频现象实例，输入两正弦波的振幅、初相位及频率观察波的合成及拍频现象(Synthesis and beat frequency wave phenomena instance, enter the two sine wave amplitude, initial phase and frequency of observation of waves synthesis and beat frequency phenomenon)

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.)

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.)

说明：  真正的3 d双树离散小波变换(DWT)的一个数据集x是使用四个严格采样实现可分3 d DWTs在平行。然后subbands四DWTs结合适当。 (The real the 3 d Doubletree discrete wavelet transform (DWT) data set x four to strict sampling separable 3 d the DWTs In parallel. The then the subbands four DWTs combined appropriately.)

wavelet transform,continuous wave let transform,discrete wavelet transform

说明：  小波标架的共轭梯度算法（Mallat，信号处理的小波导引）(Conjugate gradient algorithm for computing daul function.)

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

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)

C语言实现一维离散小波变换，通过mallat算法实现对一维信号的快速重构和分解。(C language implementation of a one-dimensional discrete wavelet transform, fast algorithm by mallat one-dimensional signal reconstruction and decomposition.)