SIFT

这是西交大客座教授美国新奥尔良大学电机系主任、信息融合领域华人带头人李晓榕写的关于跟踪和导航的书，英文版，对于搞控制和滤波的人非常有参考价值(This is a visiting professor at National Chiao Tung University in West Electric Head of the Department of the University of New Orleans, the Chinese leader in the field of information fusion李晓榕write on tracking and navigation of the book, in English, for engaging in the control and filter are very useful)

程序实现设计一单一感知器神经元以及采用神经网络拟合奇异函数。压缩包中还包含相关的参考资料。(Design a program to achieve a single sensor neurons and neural networks fitting singular function. Compressed package also contains the associated reference materials.)

Apache Server Survival Guide

calculating penalty factor for slack bus

1.灰度变换：选择一幅对比度不足的图像，对该图像进行灰度变换,增强对比度，显示增强前、后的图像以及它们的灰度直方图。 2.直方图均衡：选择一幅灰度直方图不均匀的图像，对该图像进行直方图均衡处理，显示处理前、后的图像以及它们的灰度直方图。 3.选择一幅边缘较模糊的图像，利用高通滤波器（选择或自己设计）对该图像进行边缘增强，观察增强的效果。 4.选择一幅图像，叠加零均值高斯噪声，分别利用低通滤波器、维纳滤波器和中值滤波器对该有噪图像进行滤波，显示滤波后的图 像，比较各滤波器的滤波效果。 5.选择一幅图像，叠加椒盐噪声，分别利用低通滤波器、中值滤波器对该有噪图像进行滤波，显示滤波后的图像，比较各滤波器的 滤波效果。 (err)

说明：  用Matlab编的BPSK程序，属于非常常用的一种程序(Matlab for BPSK with the procedures, are very commonly used in a process)

说明：  配合使用可以实现基于循环平稳信号的盲源分离。使用JADE和SOBI算法。自己编的(BSS based on cyclostationarity)

hough transform this project applyes hough transform on given picture in order to be able to calculate object in real world

粒子群算法OptSwarm记录每个粒子的历史最优解（粒子历史最好的适应度）以及全部粒子搜索到的全局最优解。用Wg代表全局最优解，W.,1代表每个粒子的历史最优解。粒子群初始化阶段表OptSwarm的前N行与表ParSwarm中的相同，而Wg的值为表ParSwarm中适应度值的最大值对应的行。(Particle swarm algorithm OptSwarm record the history of each particle the optimal solution (particles history best fitness), and all the particles of the search to the global optimal solution. Use Wg represents the global optimal solution, w., 1 representative of each particle history to the solution. Particle swarm initial stage OptSwarm table before the line and the table ParSwarm N is same, and the value of the ParSwarm Wg for tables in the maximum fitness value corresponding line. )

网上下的一个关于径向基函数网络应用实例，希望大家能有用(the Internet on an RBF network application examples and I hope that we can be useful)