OSTP011180

陈阳泉教授以及其他学者的有关分数阶PID方面的 论文；经典值得学习，与大家共享；仿真以Matlab为主(Papers Fractional PID aspects related to Professor Chen Yangquan and other scholars classic worth learning, shared with everyone simulation in Matlab-based)

说明：  matlab 书籍时域有限元求解电磁场，计算电磁学初学者，编写的程序代码，希望可以帮助广大网友(Matlab book time domain finite element method to solve electromagnetic field, calculation of electromagnetic beginners, compiled program code, hope to help the vast number of netizens)

SVM算法的示例程序,帮助读者理解SVM算法的使用(the use of SVU，to help reader undstander how to user this methods)

《MATLAB仿真在现代通信中的应用》（徐明远）随书光盘(The MATLAB simulation in the application of modern communication of CD attached with books (XuMingYuan) )

编程仿真连续小推力实现GTO到GEO的三阶段转移过程，其中推力器的推力大小为0.8N，轨道机动的起始点为GTO的远地点。GTO轨道的升交点赤经为0度，近地点角距为90度。 GTO轨道： ph:185km，ah：35786km，i：28.5°，GEO轨道：h：35786km，i：0°。 卫星质量为6600kg，从GTO到GEO，采用5000s的推力器。取地球半径为6378km，g取值为9.8m/s^2(The three stage transfer process from GTO to GEO is realized by simulation and continuous small thrust. The thrust of the thruster is 0.8N, and the starting point of orbital maneuver is the apogee of GTO. GTO orbit RAAN is 0 degrees, 90 degrees for the argument of perigee. GTO orbit: ph:185km, ah:35786km, i:28.5, GEO orbit: h:35786km, i:0. The mass of the satellite is 6600kg, from GTO to GEO, using the 5000S thruster. The radius of the earth is 6378km, and the value of G is 9.8m/s^2)

matlab图像处理，包括直方图均衡化，平滑滤波，拉普拉斯算子增强，及椒盐噪声的滤波处理！(failed to translate)

程序-神经网络的回归拟合——基于近红外光谱的汽油辛烷值预测(Program-Neural Network Regression Fitting-Prediction of Gasoline Octane Number Based on Near Infrared Spectroscopy)

matlab主要的函数与命令，适合菜鸟学习。电子书格式是pdf格式(matlab main functions and command)

本程序针对一类不确定性非线性系统，利用输出反馈实现系统镇定，我用simulink做的一个仿真例子。(This procedure for a class of uncertain nonlinear systems using output feedback stabilization realize system, I used to do a simulink simulation example.)

RNA 和 DNA序列模拟 基因建模 数值模拟 采用matlab 编写 能计算几千个 基因点的特性和行为(In one type of gene expression analysis, fluorescently tagged messenger RNA from different cells are hybridized to a microscopic array of thousands of complimentary DNA spots that correspond to different genes. Illuminated spots emit different color light, indicating which genes are expressed (e.g., green=control, red=sample, yellow=both). In this case study, MATLAB, the Image Processing and Signal Processing toolboxes were used to determine the green intensities from a small portion of a microarray image containing 4,800 spots. A 10x10 pattern of spots was detected by averaging rows and columns to produce horizontal and vertical profiles. Periodicity was determined automatically by autocorrelation and used to form an optimal length filter for morphological background removal. A rectangular grid of bounding boxes was defined. Each spot was individually addressed and segmented by thresholding to form a mask. The mask was used to isolate each spot from surrounding background. Individu)