algorithm

c++ and matlab 散射电流可视化、球体(c++ and matlabScattering current visualization, sphere )

惯性导航研究中的轨迹发生器，用于模拟载体的机动运动(inertial navigation study the trajectory generator to simulate carrier mobile campaign)

matlab下运行有界面，实现对特定图片的处理，可以设定参数值(run a matlab interface to achieve a specific image processing parameters can be set)

Mean Shift 这个概念最早是由Fukunaga等人[1]于1975年在一篇关于概率密度梯度函数的估计中提出来的,其最初含义正如其名,就是偏移的均值向量,在这里Mean Shift是一个名词,它指代的是一个向量,但随着Mean Shift理论的发展,Mean Shift的含义也发生了变化,如果我们说Mean Shift算法,一般是指一个迭代的步骤,即先算出当前点的偏移均值,移动该点到其偏移均值,然后以此为新的起始点,继续移动,直到满足一定的条件结束. 用matlab实现mean shift算法仿真(Mean Shift the concept was first used by Fukunaga et al [1] in 1975 in an article on the probability density function estimation of gradient raised its original meaning, as its name implies, is the offset of the mean vector, where is the Mean Shift a noun, it refers to a vector, but with the Mean Shift the development of the theory, Mean Shift the meaning has changed, if we say that Mean Shift algorithm, generally refers to an iterative steps, namely, first calculate the current point Mean offset, move the shift points to its average, and then as a new starting point and continue to move until the end to meet certain conditions. realize using mean shift algorithm matlab simulation)

这是大学毕业时设计的失真度检测仪论文，由模拟陷波器实现的剔除几波，如果改进的话，可以用数字滤波器实现，不过成本更高(It is designed for university graduation thesis distortion detector by analog notch filter removed to achieve a few waves, if improved, you can use digital filters to achieve, but higher costs)

automatic number plate using C

这是一个有关于免疫遗传算法matlab 程序(This is an on immune genetic algorithm matlab program)

一个好用的音乐播放器源码，最终程序编译后只有几十KB。VC++2010编译通过。 AppWizard has created this MusicPlayer application for you. This application not only demonstrates the basics of using the Microsoft Foundation classes but is also a starting point for writing your application.( AppWizard has created this MusicPlayer application for you. This application not only demonstrates the basics of using the Microsoft Foundation classes but is also a starting point for writing your application.)

The first scheme is based on the spatial locality of feature vectors corresponding to similar images. Learning is effected by modifying the query vector to incorporate the positive examples. The second scheme is based on “distorting” our view of the feature space. An new similarity distance between an image and the query is learned from the relevance feedback.

A hex file extremely useful for all