KNN

阵列天线的DOA估计MUSIC算法，只有几行简单的代码(DOA estimate the array antenna MUSIC algorithm, only a few lines of simple code)

图论，最小费用最大流法. 一种数学建模的实用方法，对你的比赛，和应用很有帮助(The method of graph theory, the minimum cost maximum flow.A good mathematical modeling tool, It is very helpful to your study MATLAB)

An Efficient Feature Extraction Algorithm for the Recognition of Handwritten Arabic Digits

用Mc积分的方法来计算pi的值 有明确的程序和结果(Mc integration method used to calculate the value of pi has clear procedures and results)

NTKL法可以同时检测光谱异常点、参考数据异常点及其他们共同的异常点，该方法的基本思路是基于蒙特卡洛采样，随机将样本集划分为校正集与预测集，用校正集建模，并对没参与建模的样本进行预测误差计算，进行几千次这样随机采样，每个样本点都可得到其预测误差分布。如果奇异样本在校正集中，整个模型的质量将受到影响；相反，如果奇异样本在预测集中，仅此样本的预测结果受到影响。(NTKL method can simultaneously detect abnormal spectrum and abnormal reference data points and their common abnormal point, the basic idea of this method is based on the monte carlo sampling, sample set random be divided into calibration set and prediction set, using correction modeling, modeling and participated in the samples of the prediction error calculation, a thousands of times that of random sampling, each sample point can be obtained the prediction error distribution.If singular samples in correction, the model of quality will be affected.Singular samples in predicting concentration, on the contrary, if only for the sample prediction results are affected.)

地面移动卫星信道仿真程序 考虑雨衰 阴影 和多径影响(Land mobile satellite communication channel simulation program to consider the shadow of rain attenuation and multipath effects)

和声搜索算法求解电力系统经济调度优化问题(Harmony search algorithm solve power system ecolomic dispatch optimization problem)

用matlab程序让电脑唱出世界名曲卡农(Matlab program for a computer to sing world music canon.)

说明：  基于MATLAB的非线性0-1规划的求解

位置指令为幅值为1.0的阶跃信号，r（k）=1.0。网络结构为1-4-1，高斯函数的参数值取Cj=[-2 -1 1 2]T ，B=[0.5 0.5 0.5 0.5]T 。 网络权值学习参数为η=0.30，α=0.05 。PID控制各参数的初RBF网络控制，被控对象为G（s）= 取采样时间为1ms，采用Z变换进行离散化，离散化后的被控对象为 y(k)=-den(2)*y（k-1）-den(3)*y(k-2)+num(2)*u(k-1)+num(3)*u(k-2) 始值为，kp=20， kd=0.3， ki=0.1。 (Position command for the step signal amplitude of 1.0, r (k) = 1.0. The network structure is 1-4-1, the Gaussian function parameters taken Cj = [-2-1 1 2] T, B = [0.5 0.5 0.5 0.5] T. Weight learning parameter η = 0.30, α = 0.05. PID control parameters at the beginning of each RBF network control, the controlled object is G (s) = take the sampling time is 1ms, using the Z transform discrete, discretized controlled object is y (k) =-den (2)* y (k-1)-den (3)* y (k-2)+num (2)* u (k-1)+num (3)* u (k-2) initial value, kp = 20, kd = 0.3, ki = 0.1.)