MATLABfunctionsummary

It is a useful book for manipulator robot, calculate inverse kinematic. A geometric approach in solving the inverse kinematics of puma robot. Including two main parts: Arm solution for first three joints and Arm solution for last three joints. For me, it s a good book.

应用MATLAB实现连续信号的抽样与重构仿真(Applications in MATLAB continuous signal sampling and reconstruction simulation)

入门好书《MATLAB神经网络30个案例分析》，连同源程序，许多应用范例(good book for matlab ANN)

本人基于论文理解Matlab实现的用于多目标优化的粒子群优化算法MOPSO(Particle swarm optimization algorithm.)

2D PCA IS METHOD USED FOR IRIS AND FACE RECOGNITION AN INTERSETING METHOD

说明：  用MATLAB设计及FPGA实现IIR滤波器的方法 摘要 本文介绍了IIR数字滤波器的传统设计思想与步骤及计算机辅助设计方法。并在FPGA上高效实现的低阶IIR滤波 器，其阶数低，实时响应快，适合雷达等的实时、高效处理环境。利用IIR滤波器的多相结构来实现该滤波器系统的方法，对于 四通道的情形在MATLAB上利用Simulink作了仿真, 并在目标板上对算法进行了实现,证明该系统能够同时处理四个通道的信号。(Using MATLAB Design and FPGA realization IIR Filter method Abstract This paper introduces IIR digital filter traditional design Thought and steps and CAD method. And FPGA on efficient realization low IIR filter, its order low, real response fast suitable radar real time, efficient processing environment. Use IIR filter multiphase structure realize the filter systematic method, for four channel circumstances in MATLAB on use Simulink made simulation and target board algorithm was realized proved system can simultaneously four channel signal.)

说明：  模糊聚类算法中的FCM算法，内容充实，注释详细！(Fuzzy clustering algorithm FCM algorithm, substantial and detailed comments!)

微电网并网及其控制策略研究，运用PQ控制策略进行能量的分配(Research on Grid-connected Microgrid and Its Control Strategy)

matlab实现模糊神经网络的很好的一个例子，大家可以看看。(matlab to achieve a good example of the fuzzy neural network, we can look at.)

MARKOv的应用 Step 1，求出各食品数据的增长率； Step 2，编程，使快速上升（>=0.03） ，在程序中用“2”表示；缓慢上升 (0,0.03)，在程序中用“1”表示；相对不变 0，在程序中用“0”表示；缓慢下降(-0.03,0) ，在程序中用“-1”表示；快速下降 (<=-0.03)，在程序中用“-2”表示；得到各类食品在不同时期的 ； Step 3，统计相邻增长率变化的一致的次数 ，就菜籽油而言，在2010-3-5到2011-3-15，其增长率为先快速增长后相对不变出现的次数为‘20’=1；具体42中食品的输出情况见附录； Step 4，对每一种食品，分五类进行叠加求和，分别为“先快速增长”、“先缓慢增长”、“先相对不变”、“先缓慢下降”、“先快速下降”；得到 ； Step 5，求出一步转移概率矩阵E ；即 每行的每五个数据依次与对应的 相除，得到概率矩阵E 的一行； Step 6，使用求出的一步转移概率矩阵E ，并求出不同时期的状态概率(MARKOv application Step 1, to obtain the growth rate of each food data Step 2, the programming, so fast rise (> = 0.03), in the program with " 2" slowly rising (0,0.03), used in the program " 1" indicates relatively constant 0, by the program " 0" indicates slow decline (-0.03,0), in the program by " -1" rapid decline (< =- 0.03), in the program with " -2" means get all kinds of food at different times Step 3, the same number of adjacent growth statistics change on rapeseed oil, in 2010-3-5 to 2011-3-15, Its growth rate is relatively rapid growth of the number of times after the first change occurs is ' 20' = 1 42 Output of specific food in Appendix Step 4, for each kind of food, five points are superimposed sum, respectively, " First of rapid growth," " first slow growth" , " first relatively unchanged" , " first slow down" , " first rapid decline" get Step 5, to obtain a step)