LFShirmohammedi_1

正交频分复用(OFDM)技术及其MATLAB模拟(orthogonal frequency division multiplexing (OFDM) technology and its MATLAB simulation)

使用matlab画圆，对图傅里叶变化，零频移中，反变换实验(test fft and ifft)

matlab中，对曲线拟合时指数的自动识别(matlab in, when the index on the curve fitting of automatic identification)

这是有关机器人的一个matlab代码，相信着应该对机器人专业的同学会有用！(It is about a robot matlab code, I believe that the students should be useful robot professional!)

A source code in matlab for pso(particle swarm intelligent)

绘制控制系统近似bode图，为了做自动控制原理作业时偷点懒。虽然matlab自带bode函数但是作业要求画近似的。(Drawing control system approximation bode diagram, when you steal lazy to do the job of Automatic Control Theory. Although matlab function but the job comes bode asked to draw approximate.)

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.)

the simulation provides computation of target reflectivity data in the deficient elevation domain. Simulations are implemented to test the decoupled least-squares technique for high resolutionspectral estimation of target reflectivity.all seven (7)files should be downloaded for the simulation to work.(dls3D.m,estimate.m,get2S1Data.m,getConstraints.m, getImageData.m,getPixelData.m, getSLICYData.m)

用MATLAB实现的标准卷积的算法源程序(Using MATLAB to achieve the standard convolution algorithm source code)

说明：  遗传算法（Genetic Algorithm）是模拟达尔文生物进化论的自然选择和遗传学机理的生物进化过程的计算模型，是一种通过模拟自然进化过程搜索最优解的方法，它最初由美国Michigan大学J.Holland教授于1975年首先提出来的，并出版了颇有影响的专著《Adaptation in Natural and Artificial Systems》，GA这个名称才逐渐为人所知，J.Holland教授所提出的GA通常为简单遗传算法（SGA）。(a genetic algorithm (GA) is a search heuristic that mimics the process of natural evolution. This heuristic is routinely used to generate useful solutions to optimization and search problems. Genetic algorithms belong to the larger class of evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover.)