bnb20

基于matlab的PCA人脸识别完成程序，包含特征值与特征向量的提取、训练样本以及最后的识别检验。(err)

Matlab鼠标画图,用pop-up menu选择画图标记,颜色edit记录鼠标坐标 但是功能比较简单，只能画线，不能画矩形、椭圆等 其中一个难点就是：拖动鼠标的过程中如何显示矩形/椭圆的轮廓，并且轮廓跟着鼠标指针移动。 程序的亮点： 1、可选择点、线、矩形、椭圆进行画图； 2、可选择marker、LineTyple进行画图； 3、可选择画图颜色； 4、可实时显示鼠标指针当前坐标； 5、可清除画板； 6、可保存画好的图(bmp、jpg、gif)； 7、操作比较人性化，模仿了windows画板； 8、该程序牵涉的面广，是一个很好的GUI学习资料。 (Matlab mouse drawing, with the pop-up menu select the drawing marks, color edit record mouse coordinates, but relatively simple function, can only draw a line, not drawing rectangles, ellipses, etc. One of the difficulties is this: how the process of dragging the rectangle/oval contours, and outline follow the mouse pointer moves. Program Highlights: 1, select point, line, rectangle, ellipse for drawing 2, optional marker, LineTyple the drawing 3, choose paint colors 4, real-time display the current coordinates of the mouse pointer 5, to clear the drawing board 6, save-drawn map (bmp, jpg, gif) 7, operation more user-friendly, imitating the windows drawing board 8, the program involved a wide range, the GUI is a good learning materials.)

运用KPCA方法在ORL人脸库上进行人脸识别，分类器为最近邻分类器。(KPCA method using ORL face database for face recognition, classification for the nearest neighbor classifier.)

输入相关参数，便可求得函数的二阶累积量，使得复杂计算过程得到避免(Input parameters, the function of the second order cumulant can be obtained, making complicated calculation is avoided )

主要是用于脉冲位置调制当中性能的仿真产生(Is mainly used for pulse position modulation performance simulation which generated)

matlab仿真对采集数据进行滤波的两种方法：多次平均滤波和一阶滞后滤波的比较。(matlab simulation filtering the collected data in two ways: the average number of first order lag filter and the filter comparison.)

分数阶傅立叶变换的示例程序，个人成果，仅供参考(Fractional Fourier transform of the sample program, individual results, for reference only)

基于MATLABD的线性二次型最优控制设计.二次型最优控制设计(MATLABD based on the linear quadratic optimal control design. Quadratic Optimal Control Design)

用matlab编写的Gabor滤波器，得虚部和实部(Matlab prepared by the Gabor filter, imaginary part and real part)

This file implement Gda algorithm for dimension reduction and clustering techniques. Dimension reduction, Clustering.