硬币识别直径

分东西和南北两个路口模拟交通三色信号灯的亮灭控制(East and West and North-South two intersection points simulated three-color traffic signal control of bright eliminate)

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LMS algorithm demonstration in matlab, quite useful

It s sudoku implemented in Matlab

蒙特卡洛方法（Monte Carlomethod）非线性反演方法及应用(Monte Carlo method (Monte Carlo method）non-linear inversion method and its application)

测试可以跑，根据自己情况修改下函数即可. NSGA-III 首先定义一组参考点。然后随机生成含有 N 个（原文献说最好与参考点个数相同）个体的初始种群，其中 N 是种群大小。接下来，算法进行迭代直至终止条件满足。在第 t 代，算法在当前种群 Pt的基础上，通过随机选择，模拟两点交叉（Simulated Binary Crossover，SBX）和多项式变异 产生子代种群 Qt。Pt和 Qt的大小均为 N。因此，两个种群 Pt和 Qt合并会形成种群大小为 2N 的新的种群 Rt=Pt∪Qt。 为了从种群 Rt中选择最好的 N 个解进入下一代，首先利用基于Pareto支配的非支配排序将 Rt分为若干不同的非支配层（F1，F2等等）。然后，算法构建一个新的种群St，构建方法是从 F1开始，逐次将各非支配层的解加入到 St，直至 St的大小等于 N，或首次大于 N。假设最后可以接受的非支配层是 L层，那么在 L+ 1 层以及之后的那些解就被丢弃掉了，且 St FL中的解已经确定被选择作为 Pt+1中的解。Pt+1中余下的个体需要从 FL中选取，选择的依据是要使种群在目标空间中具有理想的多样性。(The test can run and modify the function according to its own situation. NSGA-III first defines a set of reference points. Then the initial population containing N individuals (preferably the same number of reference points as the original literature) was randomly generated, where N was the size of the population. Next, the algorithm is iterated until the termination condition is satisfied. On the basis of current population Pt, the algorithm simulates two-point crossover (SBX) and polynomial mutation to produce offspring population Qt by random selection.)

供做算法研究人员参考，迭代自组织数据分析，采用的是脉冲对消法，关于神经网络控制，进行波形数据分析,数学方法是部分子空间法。

用SCA算法实现时间同步和载波频率偏移。载波频率偏移通过训练序列实现(SCA algorithm with time synchronization and carrier frequency offset. Carrier frequency offset achieved by training sequence)

说明：  最新的matlab贝叶斯网络工具箱FullBNT-1[1].0.5.zip(Latest matlab Bayesian network toolbox FullBNT-1 [1] .0.5. Zip)

两个数值实验的matlab编程实现。题目分别1是利用循环语句，计算数列根号5 ，根号下根号5 ，根号下根号下根号5…的极限，要求误差小于 10负8次方。 2利用级数pi=1-1/3+1/5-1/7+...可计算出无理数pi的近似值(Two numerical experiments matlab programming. Title 1 is the use of loop were calculated series roots and 5, roots and root number under 5, roots and root, root number under number 5 ... the limits of error of less than 10 required a negative 8th power. 2 using series pi = 1-1/3+1/5-1/7+ ... calculate the approximate irrational number pi)