CooperativeDiversity

CROSS-RANGE IMAGING, Program performs slow-time compression to save PRF

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.)

PSO与SVM如何结合及其实际应用 是一篇把这两个算法结合使用的很好文章(PSO and SVM and its practical application of how to combine these two algorithms is a combination of a good article)

此程序为在MATLAB环境下编写的模糊控制模块，通过模糊判断改变ＰＩＤ控制的参数，实现模糊ＰＩＤ控制。(This program is written in the MATLAB environment, fuzzy control module to change the PID control parameters, the fuzzy PID control, fuzzy judgment.)

精通MATLAB计算科学书源代码，原书正版CD第二章源代码(Proficient in computer science book MATLAB source code, the original book source code CD to Chapter)

希尔伯特变换实现了SSB调试，画出信号的时域和频域的图象只管观察(Hilbert transform SSB debugging, draw the signals in time domain and frequency domain image just observed)

color code segentation detection

FIR低通滤波器 汇编(FIR low-pass filter compilation)

说明：  一种快速有效、性能可靠的信号重构算法是压缩感知理论的核心部分，对于 这部分内容，许多卓有成效的研究工作正在陆续展开。从压缩感知理论提出至今， 已经出现了多种稀疏信号的重构算法。重构算法主要可以归结为三大类：贪婪算 法，凸松弛算法和组合算法。这里主要是SP算法(A fast and efficient, reliable signal reconstruction algorithm is the core of compressed sensing theory, for this part, much fruitful research work is carried out successively. From the compressed sensing theory so far, there have been many sparse signal reconstruction algorithm. Reconstruction algorithm can be summarized into three main categories: the greedy algorithm, convex relaxation algorithms and combinatorial algorithms. This algorithm is mainly SP)

利用matlab实现burg算法的程序，不是调用pburg函数，希望能帮助要做课程作业的童鞋们。(The matlab burg algorithm program, not call pburg function, hoping to help the children ' s shoes to do course work.)