freqsyncyclicprefix

说明：  mimo_ofdm 仿真程序 已验证成功(mimo_ofdm simulation program has been successfully verified)

直流电机的转速，电流双闭环控制simulink仿真，包括整流桥(DC motor speed and current closed-loop control simulink simulation, including the bridge rectifier)

重复控制的实现。提供matlab源码实现，及simulink实现。(RepetitiveControl realization.)

matlab在数学建模中的应用，有许多有用的算法，可以帮助需要参加数学建模工作的人快速建立模型并求解(matlab mathematical modeling, there are many useful algorithms, people need to participate in the mathematical modeling can help to quickly build the model and solving)

ask调制模块，matlab，m文件，用m文件写的ask调制的模块(ask modulation module, matlab, m file, m file to write the module ask modulation)

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.)

本程序为利用给定节点，求未知节点插值法，包括拉格朗日插值法和牛顿向前插值法(This procedure for the use of a given node, seeking the unknown node interpolation method, including the Lagrange interpolation method and Newton' s forward interpolation)

说明：  基于Matlab编写的手写字符特征提取代码(Matlab-based feature extraction handwritten character written in the code)

求出语音mel倒谱系数的matlab代码，返回mfc(function mfc=mfcc(x) )

毫米波图像存在分辨率低的缺点，该程序在WRLA算法的基础上，进一步采用投影算法，能有效改善毫米波图像的分辨率(Images acquired from Passive Millimeter-Wave (PMMW) radiometer have poor resolution due to limited aperture dimension. Therefore, Super-Resolution Algorithm (SRA) is a key component for PMMW imager. SRA realizes spectrum extrapolation, however, spectrum in-band is deteriorated too. Wiener-Richardson-Lucy Algorithm (WRLA) recovers spectrum in-band by Wiener filter, and extrapolates spectrum out-of-band by Richardson-Lucy Algorithm (RLA). WRLA can avoid spectrum deterioration in passband, but its ability for spectrum extrapolation is limited also. We propose an improved algorithm to solve this problem. This algorithm, which has built constraints according to characteristics of PMMW imaging, uses Projection-Onto-Convex-Sets (POCS) technique to enhance the WRLA s performance, so it is termed as POCS-WRLA.)