mergesortedvectors

说明：  用MATLAB编写与仿真了MSK信号，其中调制解调都有，很有用(Written and simulated using MATLAB MSK signal modulation and demodulation of which are very useful)

在阵列信号处理中，一种很经典的信号波达角方向估计方法：MUSIC（多重信号分类）算法。该程序中有三个频率的信号，经过此算法可很好地分辨出这三个信号。(In array signal processing, a classic signal the direction of arrival angle estimation method: MUSIC (multiple signal classification) algorithm. The program has three frequency signals, by using this algorithm,and you can well distinguish these three signals.)

利用matlab进行离群点检测，包含KNN,LOF,k-means方法(Using MATLAB to detect outliers, including KNN, LOF and K-means methods.)

心电数据的滤波代码，已经调试通过，可以滤出工频干扰，基线飘移。谢谢合作(ECG data filtering code debugging has been passed, and labor-frequency interference filters, baseline drift. Thank you for your cooperation)

machine dc mfile

本工具箱主要为学习数学建模和参加中国大学生数学建模竞赛的同学而制作。汇集了 数学建模常用的最优化、微分方程、数据拟合、统计等方面的计算工具，包括我们自 编的补充工具。工具箱还汇集了96-99中国大学生数学建模竞赛题解MATLAB程序。本 工具箱也可供使用MATLAB作数值计算的学生、教师和科技人员参考。(This toolkit is mainly mathematical modeling study and participated in the China Mathematical Contest in Modeling the production students. A collection of commonly used mathematical modeling optimization, differential equations, data fitting, statistics and other aspects of computational tools, including our self complementary tool. The toolbox also brings together 96-99 China Mathematical Contest in Modeling problem solution MATLAB. The toolkit is also available using MATLAB for numerical calculation of the students, teachers and technology officers.)

matlab gui 资料学习,非常值得一看，word版(matlab gui reference)

说明：  多目标遗传算法是NSGA-II[1]（改进的非支配排序算法）,该遗传算法相比于其它的多目标遗传算法有如下优点：传统的非支配排序算法的复杂度为 ，而NSGA-II的复杂度为 ，其中M为目标函数的个数，N为种群中的个体数。引进精英策略，保证某些优良的种群个体在进化过程中不会被丢弃，从而提高了优化结果的精度。采用拥挤度和拥挤度比较算子，不但克服了NSGA中需要人为指定共享参数的缺陷，而且将其作为种群中个体间的比较标准，使得准Pareto域中的个体能均匀地扩展到整个Pareto域，保证了种群的多样性。（消除了共享参数）。(Multi-objective genetic algorithm is nsga-ii [1] (improved non-dominant sorting algorithm), which has the following advantages compared with other multi-objective genetic algorithms: the complexity of the traditional non-dominant sorting algorithm is, while the complexity of nsga-ii is, where M is the number of objective functions and N is the number of individuals in the population.The introduction of elite strategy to ensure that some good individuals in the evolutionary process will not be discarded, thus improving the accuracy of the optimization results.The comparison operator of crowding degree and crowding degree not only overcomes the defect that NSGA needs to specify the Shared parameter artificially, but also takes it as the comparison standard between individuals in the population, so that individuals in the quasi-pareto domain can uniformly expand to the whole Pareto domain, ensuring the diversity of the population.(eliminating Shared parameters).)

说明：  介绍了matlab 语言及其在电子信息工程中的应用(Describes the matlab language and its application in electronics and information engineering)

Computing the BER for MIMO system with MINIMUM MEAN SQUARE ERROR Equalization in a Rayleigh fading channel.