Diophantine

FFT的matlab程序，老师编的，很实用。

光流法检测运动物体的基本原理是：给图像中的每一个像素点赋予一个速度矢量，这就形成了一个图像运动场，在运动的一个特定时刻，图像上的点与三维物体上的点一一对应，这种对应关系可由投影关系得到，根据各个像素点的速度矢量特征，可以对图像进行动态分析。(Optical flow detection)

对极限学习机的数据的补充。This paper has demonstrated that ELM can be used efficiently in many applications, however, two more interesting aspects are still open: the universal approximation capability9 of ELM and the performance of ELM in sparse high-dimensional applications, which are currently under our investigation.(Extreme Learning Machine data supplement.)

matlab绘制图形完成后，在句柄窗口实现局部放大，通过鼠标键盘的操作来选择放大区域(matlab graphics rendering is completed, the handle of the window to achieve local amplification, through the operation of mouse and keyboard to select the magnified area)

盖尔圆法进行信号源数估计，方面不错。也可应用于聚类算法。(Source number Gail round signal estimation method, good aspects. Can also be applied clustering algorithm.)

mpak simulation modulation and demodulation

the code is to track the lips. which need to be marked by red color. the code tracks the red color of the lips and thus the lips indirectly. such system can be very much useful for audio visual departments

GPS_SDR:GPS软件接收机源码，包括从中频数据获取到捕获、跟踪、解码、定位和界面显示。(GPS_SDR: GPS software receiver source, including data acquisition from the IF to the acquisition, tracking, decoding, positioning, and screen displays.)

In 1960, R.E. Kalman published his famous paper describing a recursive solution to the discretedata linear filtering problem [Kalman60]. Since that time, due in large part to advances in digital computing, the Kalman filter has been the subject of extensive research and application, particularly in the area of autonomous or assisted navigation. A very “friendly” introduction to the general idea of the Kalman filter can be found in Chapter 1 of [Maybeck79], while a more complete introductory discussion can be found in [Sorenson70], which also contains some interesting historical narrative.(In 1960, R. E. Kalman published his famous paper describ ing a recursive solution to the discretedata li near filtering problem [Kalman60]. Since that time, due in large part to advances in digital computi Vi, the Kalman filter has been the subject of extens ive research and application. particularly in the area of autonomous or assis ted navigation. A very "friendly" introductio n to the general idea of the Kalman filter can be f ound in Chapter 1 of [Maybeck79] while a more complete introductory discussion can be found in [Sorenson70] which also contains some interesting historic al narrative.)

结合了分页显示、拖拽换位、删除及动画效果，长按后可进行拖拽，并在拖拽的移动过程中有补位的动画效果，可在拖拽过程中换页。自定义点击目标的可删除、可移动的属性。(Combines paging display, drag transposition, delete, and animation effects, long press can drag and drag to move the process to fill the seats have animation, can change the course page in drag. Custom Click goals can be deleted, movable property.)