kanfao

Henon吸引子是混沌和分形的著名例子,迭代模型为xk+1=1+ax2k+byk,yk+1= xk.最常见的参数取值为a=1.4,b=0.3 .(The Henon attractor is chaotic and fractal famous example of the iterative model xk+1 = 1+ ax2k+ byk yk+1 = xk. The most common parameter values ​ ​ a = 1.4, b = 0.3)

Matlab环境下利用Daubechies小波族中的db10小波对散斑退化图像进行了压缩数值仿真研究。研究表明：阈值以及分解层次的选取影响着图像压缩的质量。(Matlab environment using Daubechies wavelet tribal db10 wavelet the withdrawal of speckle image compression for the numerical simulation. Research shows : the threshold level of decomposition is influenced by the quality of image compression.)

本程序为无线通信中ofdm的一个仿真代码，采用qpsk的调制方式，适合初级学生学习。(This program is a simulation code ofdm wireless communications, using qpsk modulation, suitable for primary students.)

Quinlan的决策树程序C4.5（M语言编写）(the program for decision tree C4.5 purposed by Quinlan )

建立模型参考自适应系统(MRAS)来估计转子磁链，最后通过Matlab／Simulink仿真与基于DSP的无速度传感器异步电动机矢量控制实验(Model reference adaptive system (MRAS) to estimate the rotor flux, and finally through Matlab/Simulink Simulation and DSP-based induction motor speed sensorless vector control experiments)

The most critical problem to solve is how to design and tune the power electronic components in the inverter to cooperate in the best manner possible. How can voltage transients, oscillations and losses be reduced to a minimum? Could this be done with help of snubber circuits?

关于TSP模拟退火&遗传算法&相应的MATLAB算法程序( tsp Genetic algorithm and simulated annealing and corresponding MATLAB algorithm procedures)

matlab符号运算的电子书籍。对想学习matlab的同学比较有用(the matlab symbolic computation electronic books. Useful to the students want to learn matlab)

Learning_random.m : 随机选择样例，从（90）pool里随机选择样本，删除版本空间树的数量 activeLearning.m:根据最大熵原则,从pool里选择样本，删除版本空间树的数量 getlabel.m:根据树和测试样例，得到根据该树得到的类标 getTrees.m:从提供的大量树结构(随机生成的)中，随机挑选一定数量的树(如果该树的叶子节点无类标随机添加) RandomCreateTree_d_unbalance:根据样本点割点中的非平衡割点建造树， RandomCreateTree_d_all.m:根据所有样本点的割点建造树 randomdata.m：给定属性取值，造数据 randomselect.m:从数据中随机选择一部分作为 showTree.m:显示树的结构 test.m:给出树，测试样例，得到正确率(Learning_random.m: randomly selected sample, randomly selected sample from (90) pool the The deleted version space tree quantity activeLearning.m: selecting a sample from the pool based on the principle of maximum entropy, delete the number of version space tree getlabel.m: According to the tree and the test sample obtained according to the class standard getTrees.m the tree: from the tree structure (randomly generated), randomly selected a certain number of trees (the leaves of the tree node class marked randomly adding ) RandomCreateTree_d_unbalance: According to the sample point cut point unbalanced cut point construction tree, RandomCreateTree_d_all.m: construction of the tree randomdata.m all sample points cut point: given the value of the property, manufacturing data randomselect.m: random data Select as part showTree.m: tree structure test.m: tree, the test sample is given to get the correct rate)

基于MATLAB／Simulink环境下的PID参数整定(PID parameters based on MATLAB/Simulink environment setting)