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小生境遗传算法用于优化问题，得到了比遗传算法更好的效果(Niche genetic algorithm for optimization problems, get better results than the genetic algorithm)

无码间串扰传输条件，程序段经过仿真后所呈现的图形非常完美，大家可以试试看。(No intersymbol crosstalk transmission conditions, procedures, after the segment through the simulation of the graphics rendering is perfect, we can give it a try.)

用matlab 做的图像畸变校正源程序.主程序主要是做了一个图像处理的界面，并且实现图像的几何畸变校正，颜色畸变校正和图像模糊处理。外加几个子程序(Using matlab to do image distortion correction source main program is an image processing interface and image geometric distortion correction, color distortion correction and image blur processing. Plus several subroutines)

说明：  层次分析法matlab程序及说明书，是指将与决策总是有关的元素分解成目标、准则、方案等层次，在此基础之上进行定性和定量分析的决策方法。(Analytic hierarchy process (AHP) matlab program and specification is a decision-making method that decomposes the elements related to decision-making into objectives, criteria, schemes and other levels, and carries out qualitative and quantitative analysis on this basis.)

射频方面的技术文档:天线测试手机射频特性测量解决方案及应用(RF technical documents: RF characteristics of mobile phone antenna test measurement solution and application)

该程序实现了雷达信号下降沿的检测不用知道雷达脉冲信号的结束时间信噪比不可以太小(The program achieved a falling edge detection of radar signals do not know the time of the radar pulse signal the end of the signal to noise ratio can not be too small)

快速谱峭度工具箱，由法国人Antoni编写(Fast spectral kurtosis toolbox, written by French Antoni)

说明：  使用matlab程序编成的一个猜数的小游戏(Matlab program compiled using a guessing game)

代码实现了各种方法的功率谱估计，包括MUSIC,AR,MUDV(Code of the various methods of power spectrum estimation, including MUSIC, AR, MUDV)

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.)