DSSS

根据对真空蒸发镀膜的分析，在40×40的范围内分别蒸 发：1000、5000、10000、20000、30000个粒子。  利用2维数组记录每个点的粒子数。  初始粒的横纵坐标为0～40的均匀分布。  能量为（15，3）的正态分布。  在基体表面自由行走时损失1的能量。  若该点有粒子，即与其他粒子相遇时损失3的能量。  由低处向高处扩散，每扩散一层，损失4的能量，由高处 向低处扩散，损失3的能量。  当粒子的能量小于等于0时停留下来，该点的粒子数加1。  临界核的尺寸为10个粒子。  根据每个点粒子个数的不同，以不同的灰度显示这些点。 点越亮，则表示该点的膜越厚。  以图形方式显示粒子初始能量的正态分布情况(Based on the analysis of the vacuum evaporation coating, respectively, in the range of from 4040 evaporated: 1000,5000,10000,20000,30000 particles.  each point using 2-dimensional array to record the number of particles. The  initial grains transverse and longitudinal coordinates of a uniform distribution of 0 to 40. The  energy as a normal distribution (15,3).  1 energy losses in the substrate surface to walk.  point particles that 3 energy loss in the encounter with the other particles.  by the lower diffusion tops every diffusion layer, a loss of 4 energy diffusion from high to low, the energy loss of 3.  When the energy of the particles is less than or equal to 0:00 stay down, add 1 to the number of particles that point.  critical nucleus size of 10 particles.  these points, depending on the number of particles of each point is displayed in a different shade. Point, the brighter, the thicker the point of the fi)

对一幅图像使用最大类间分割算法，对其惊醒分割处理，得到二值图像(The segmentation algorithm between categories )

说明：  蒙特卡洛，标准历史模拟法计算MATLAB编程计算股票VaR(Monte Carlo, standard historical simulation method to calculate VaR)

能够输入至多50个电话号码，输入用户姓名，可以查找到相应的电话号码(Be able to enter up to 50 phone numbers, enter the user name, you can find the appropriate telephone number)

Ear recognition in matlab

对波动光学中的衍射进行三大衍射实验的计算机仿真(The diffraction of wave optics for three big diffraction experiment of computer simulation )

Field Antenna Handbook

随机信号分析MATLAB的重要的仿真实例，有几个常用的仿真源代码，希望能够对修这门课的学生有用。(The document contains some useful functions some important Simulation examples of random signal and i think it is Practical。)

基于加权LS-SVM的非线性系统内模控制的仿真程序，由于辨识信号采用的都是随机信号，不是数值固定的信号，所以程序每次运行的结果都可能有所不同(Emulator mode control based on weighted LS-SVM nonlinear systems identification signal are random signal, not the value of the fixed signal, so the program each time you run the results are likely to differ)

low pass filtering and global communication and wiener filter