SAR

本文介绍了局部放电信号的消噪方法，主要基于改进的小波消噪和序列脉冲分析手段来实现。(This paper presents a de-noising method for partial discharge (PD) online monitoring of transformers. The method is based on an improved wavelet de-noising approach and a pulse-sequence analysis method.)

数字全息和计算程式 计算全息图的制作和再现过程主要分为以下几个步骤： 1抽样。得到物体或波面在离散样点上的值。 2.计算。计算物光波在全息平面上的光场分布。 3.编码。把全息平面上光波的复振幅分布编码成全息图的透过率变化。 4.成图。在计算机控制下，将全息图的透过率变化在成图设备上成图。如果成图设备分辨率不够，再经光学缩版得到实用的全息图。 5.再现。这—步骤在本质上与光学全息图的再现没有区别。 (Digital Holography and CGH for calculating the production and reproduction process is divided into the following steps: 1 sampling. Be objects, or wavefront-like point in the discrete value. 2. Calculated. Calculation of complex light plane in the holographic optical field distribution. 3. Coding. The hologram plane the complex amplitude distribution of light into a hologram coding changes in the transmittance. 4. As Fig. Under the control of the computer, the hologram transmittance change in the mapping device mapping. Mapping equipment, if not resolution, then reduced by the optical version of a hologram to be practical. 5. Reproduction. This is- these in essence a hologram and the optical reproduction is no different.)

说明：  LeGall(5，3)小波滤波器，其计算复杂度小、存储开销低、压缩效率高，已被JPEG2000标准采用。提升小波实例c语言实现(Lifting Wavelet Example C Language Implementation)

基于MATLAB的GS算法的高斯光束整形设计(Designof BinaryOptical Element withMATLAB)

提升小波变换程序， %LWT Lifting wavelet decomposition 1-D. % LWT performs a 1-D lifting wavelet decomposition % with respect to a particular lifted wavelet that you specify.(lifting wavelet transform procedures% Local Walsh Transform Lifting wavelet decomposition 1-D. % Local Walsh Transform performs a 1-D lifting wavelet decomposition% with respect to a particular lifted wavelet that you specify.)

任意阶daubechies小波函数的构造，包括尺度函数和小波函数以及滤波器系数的构造(arbitrary order PG wavelet function, including scaling function and wavelet function and the structure of the filter coefficients)

实现盲源信号的分离，在一个信号源中提取出有用的信号。(Blind source signal separation, in a signal source to extract useful signals.)

本文实现基于贝叶斯(BAYES)阈值的小波(WAVELET)图像去噪算法，相比较其它的小波去噪算法而言，效果非常好(This realization based on Bayesian (BAYES) Threshold the wavelet (WAVELET) image denoising algorithm, compared with other wavelet denoising algorithm, the effect was very good)

数字图像获取, 处理及实践应用源代码——很多有用的图像处理的源代码：图像显示（原图、抖动），图像增强（灰度变换、直方图均衡、多种滤波器、伪彩色增强等），图像复原（运动模糊、逆滤波等等），图像变换（傅立叶变换、快速傅立叶变换、离散余弦变换、沃尔什变换、霍特林变换、小波变换、小波反变换），图像编码（霍夫曼编码、香浓-费诺编码、算术编码、位平面编码等），图像识别。(Digital image acquisition, processing and practical application source code- a lot of useful image processing source code: Image Display (image, jitter), image enhancement (gray-scale transformation, histogram equalization, multi-filter, pseudo-color enhancement, etc. ), image restoration (motion blur, inverse filtering, etc.), image transform (Fourier transform, fast Fourier transform, discrete cosine transform, Walsh transform, Hotelling transform, wavelet transform, wavelet transform), image coding (Huffman coding, Shannon- Fenno coding, arithmetic coding, bit plane coding, etc.), image recognition.)

ECG feature wavelet transform