相关系数

说明：  AForgeNet 是基于.net框架使用C#高级面向对象语言设计开发的专门为开发者和研究者学习和使用的开源图像处理类库，包括计算机视觉与人工智能，图像处理，神经网络，遗传算法，机器学习(AForgeNet is an open source image processing class library designed and developed for developers and researchers based on. net framework using C # advanced object-oriented language. It includes computer vision and artificial intelligence, image processing, neural network, genetic algorithm and machine learning.)

图像处理入门编程 包括动态跟踪和视频处理 有对应的任务指导书(image processing include the mission book)

说明：  Tent混沌系统的分析图。对就是分析图系列，没错。Tent。。。。。。(The analysis diagram of Tent chaotic system. That's the analysis of the graph series, that's right. Tent)

基于矢量匹配法的快速实现程序，工程中较常用(Vector-based matching method for the rapid realization process, more commonly used engineering)

采用FDTD时域有限差分法计算电磁波的传播问题等,(The finite difference time-domain (FDTD) method is used to calculate the propagation of electromagnetic wave.)

电压跌落是最严重的动态电能质量问题之一， 精确定位电压跌落起止时间是应对电压跌落问题的 重要前提和基础。由于电压采样信号往往有噪声分 量，现有的方法在定位电压跌落的起止时间时存在 局限性。本文提出利用多小波变换及相邻系数去噪 的电压跌落定位方法。多小波兼有对称性、正交性、 有限支撑性和二阶消失矩等优异的信号处理性能， 利用GHM多小波可以准确定位电压跌落起止时间。 多小波变换系数在每层之间具有对应关系，多小波 相邻系数将紧相邻的若干个系数作为一个整体来确 定阈值，考虑了系数之间的相关性，能获得更好的 去噪效果。通过 Matlab 进行仿真验证，仿真结果表 明，所提出的方法的正确性。 (Voltage sag is one of the most serious dynamic power quality problems. Critical start-time and end-time are important indices for voltage sags. But the sampling signals often have noisy component, the locations of start-time and end-time are hard to get. Wavelet is an effective tool for those non-stationary signal processing and has been used in this field. Local feature in the signal can be enlarged after the transformation using the scalar wavelet. But scalar wavelets cannot contain orthogonality, symmetry, compact support and higher order of vanishing moments simultaneously. In this thesis, multi-wavelets GHM is used to detect and locate power quality disturbances. Multi-wavelets offer many excellent properties such as the same approximation order but more compact support. The dependence of the multi-wavelets coefficients varies with the level, so neighboring coefficien)

基于Hough 变换的SAR 图像舰船尾迹检测方法。该文引进了K均值聚类方法,将这些点集归类,归类后的每一类的类心能很好的代表一条尾迹,实验结果表明方法是有效的。(Hough transform based on SAR images of ship wake detection. The introduction of the K-means clustering method to classify these points, is classified in each category after the class on behalf of the heart can be a good wake, experimental results show that the method is effective.)

curve generation using hermit concept

根据曲率求图像分割的方法，可以在matlab下运行。(According to the curvature of the methods for image segmentation, you can run.)

说明：  QT webview浏览器相关开发，简单webview应用开发(QT WebView browser related development, simple WebView application development)