multi_user_MIMO

matlab中正态分布曲线的产生以及正态分布样本经验分布曲线 EDF 和 分布函数曲线CDF 曲线的对比(matlab in the production and the normal distribution curve normal distribution curve for Empirical distribution function curve of EDF and CDF curve comparison)

在matlab中，采用模糊神经网络对监控水资源(In matlab using fuzzy neural network monitoring water)

关于距离扩展目标-MN检测方法的matlab实现程序(Matlab on goal from the extended-MN detection method to achieve program)

Project about system for detection of wireless signals.

matlab数字图像处理，关于角点特征检测的内容(matlab digital image processing, feature detection on the corner of contents)

涡轮风扇发动机从正常运行至失效的全寿命采集的实验数据，对于研究涡轮风扇发动机的故障的预测及性能评估想必有用。(Turbofan engine failure from normal operation to the whole life of the experimental data collected for the study of turbofan engine failure prediction and performance evaluation must be useful.)

利用matlab计算探月卫星速度的教程 清晰易懂~(Calculated using matlab tutorial lunar satellite speed lucid ~)

晶闸管控制串联电阻在500kv电力系统的matlab仿真中的应用。(Modeling and simulation of 500kv power system.The theoretical ground and design realization of alternating current power lines of the new type- Controllable Flexible A.C. Transmission Systems (CFACTS) are considered. Earlier lines of such type had been known as Controlled Self- Compensating High Voltage Transmission Power Lines (CSHVL), as well as Controlled Compact Transmission Power Lines. The CFACTS design principles and the basic CFACTS design directions are implemented. The basic characteristics of CFACTS (500kV) which are studying have great prospects. CFACTS(10, 35, 110 kV) which already built and maintained. )

基于SVR的线性系统内部模型辨识建模及校验的仿真程序， 由于辨识信号采用的都是随机信号，不是数值固定的信号，所以程序每次运行的结果都可能有所不同。(Based the SVR system of linear internal model identification modeling and verification simulation program identification signal are random signal, not the value of the fixed signal, so the program each time you run the results are likely to differ.)

粒子群优化算法（PSO）是一种基于种群的随机优化技术，由Eberhart和Kennedy于1995年提出。粒子群算法模仿昆虫、兽群、鸟群和鱼群等的群集行为，这些群体按照一种合作的方式寻找食物，群体中的每个成员通过学习它自身的经验和其他成员的经验来不断改变其搜索模式。 (Particle swarm optimization algorithm (PSO) is a population based stochastic optimization technique, put forward by Eberhart and Kennedy in 1995. Particle swarm optimization (pso) algorithm on insects, herds, flocks and schools of fish swarm behavior, and these groups to find food in a cooperative way, each member of the group itself by learning experience and the experience of the other members to continuously change its search pattern.)