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随机微分方程工具，matlab程序....(sde toolbox)

本代码实现了通过模糊控制进行倒车的例子，可以完美运行，是智能控制方面学习的好资料。(The code examples performed by reversing the fuzzy control, can perfectly run, is good information intelligent control aspects of learning.)

说明：  利用MATLAB和差分进化算法（DE）求解旅行商问题（TSP）(Using MATLAB and DE to solve TSP)

说明：  用阈值迭代分割算法对图像进行二值化（matlab）(Iterative segmentation algorithm with the threshold value of the image binarization (matlab))

系统辨识与自适应控制 MATLAB仿真(System Identification and Adaptive Control of MATLAB simulation)

gilbert strang Computational Science and Engineering

Inverted pendulum in cart controled by torque. It contains regulators: one to move it, second to stabilize pendulum, and last to stabilize the cart

混合蛙跳算法程序，采用1、若干次运行取最优 2、增加进化代数maxgen 3、加大种群规模popsize。三种方法来可有效克服随机初始化带来的局部极小问题(Shuffled frog leaping algorithm, using one, several runs to take the best two, increasing evolution algebra maxgen 3, to increase the population size popsize. Three ways to effectively overcome local minima caused by random initialization problem)

Simple multiobjective optimization

M=63 J=(M-1)/2 Wp=0.5*pi Ws=0.6*pi Np=100 Ns=100 weightp=1 weights=100 通带和阻带的加权系数 WpN=linspace(0,Wp,Np) WsN=linspace(Ws,pi-0.05,Ns) Wm=[WpN WsN] p=[ones(1,50),ones(1,50)/2] d=[p,zeros(1,Ns)] W=diag([weightp*ones(1,Np),weights*ones(1,Ns)]) C=cos(Wm*[0:J]) Q=diag(cos(Wm*0.5)) g=(W*Q*C)(W*d) g=g h=(g(J:-1:2)+g(J+1:-1:3))/4 h=[g(J+1)/4 h g(1)*0.5+g(2)/4] h=[h fliplr(h)] W=linspace(0,pi-0.1,512) H=freqz(h,1,W) plot(W/pi,20*log10(abs(H))) (filter design)