一个一个重构算法--子空间追踪方法调试工具

此代码仿真了一个语音输入输出系统，语音信号经过AD转换后，经过DSSS调制解调后，通过DA转换还原输入的声音，每一步的的波形都可以观测，对实际DSSS系统设计有很大的参考价值(This code simulation of a voice input and output systems, speech signal after AD conversion after DSSS modem through DA conversion to restore the input voice, each step of the waveform can be observed, the actual design of DSSS systems have great reference value)

This function is used to evaluate the max height and the max distance of a projectile and plot the trajectory. Inputs v0 : The initial velocity in m/s theta: The angle at which the projectile is fired in degrees Outputs hmax : The maximum hieght in m dmax : The maximum distance in m

BP神经网络的预测应用，结果表明神经网络有良好的预测精度，对实际生活有指导作用(The prediction of BP neural networkThe results show that neural network have good precision, and to the actual life has a guiding role )

基于遗传算法的非线性方程的拟合，实现高拟合质量，不需要输入初值。(Fitting nonlinear equations based on genetic algorithms to achieve high quality fit, do not enter the initial value.)

cdma simulation using mat lab code

电力系统15机经济负荷分配；降维；遗传算法(power system 15 bus economic load dispatch genetic algorithm)

说明：  matlab实验 用给定的多项式，y=x3-6x2+5x-3，产生一组数据(xi,yi，i=1,2,…,n),再在yi上添加随机干扰(可用rand产生(0,1)均匀分布随机数,或用rands产生N(0,1)分布随机数)，然后用xi和添加了随机干扰的yi作的3次多项式拟合，与原系数比较。 如果作2或4次多项式拟合，结果如何？ (matlab experiment with a given polynomial, y = x3-6x2+5 x-3, generated a set of data (xi, yi, i = 1,2, ..., n), then add random noise in yi (available rand generation (0,1) uniformly distributed random number, or rands generated N (0,1) random numbers), then xi and yi to add a random disturbance polynomial fitting for the three times, compared with the original coefficient . If 2 or 4 times for polynomial fitting, the result?)

this the code of hybrid big-bang big-crunch algorithm in matlab

通过有针对性的训练，方便而快捷地帮助初学者解决Matlab编程中的问题(There are solutions for the basical problems which are very common in the program design using Matlab, and it is rather convenient.)

说明：  潮流计算的matlab编程，分别试了PQ分解法，牛拉法，高斯赛德尔法(The matlab programming of power flow calculation has tried PQ decomposition method, Niula method and Gauss Seidel method respectively.)