period_lamdaBragg

对二阶被控对象实现直接自适应模糊控制器设计与仿真(Implementation of the Second accused of objects Direct Adaptive Fuzzy Controller Design and Simulation)

这是一个粒子群算法（pso）的MATLAB源程序(This is a particle swarm optimization (pso) the MATLAB source code)

matlab拓展编程，本书以matlab扩展编程及其应用实例为主线，以matlab与c、visual basic、excel、网络和硬件接口为核心，采用图文并茂的方式，系统介绍了matlab的新特性(matlab to expand programming, book matlab expansion of the programming and its application examples the main line, as the core of matlab and c, visual basic, excel, network and hardware interface, using illustrated the way, the system introduces the new features of the matlab)

Matlab code for speech recognition

Different Modulation schemes are here! like ask, fsk, psk etc!

clear all I=imread( lena.bmp ) figure imshow(I) I2=imrotate(I,-4, bilinear ) 逆时针旋转4度 figure imshow(I2) I3=fliplr(I) 垂直镜像 figure imshow(I3) I4=imresize(I,0.5, bilinear ) 缩小为原图的1/2 figure imshow(I4) A=double(I) 转换为double类型 计算7个不变矩 [nc,nr]=size(A) [x,y]=meshgrid(1:nr,1:nc) 得到网格 x=x(:) y=y(:) A=A(:) m.m00=sum(A) if m.m00==0 m.m00=eps end m.m10=sum(x.*A) m.m01=sum(y.*A) 计算均值 xmean=m.m10/m.m00 ymean=m.m01/m.m00 计算中心矩(li9_23.rar cm.cm00=m.m00 cm.cm02=(sum((y-ymean).^2.*A))/(m.m00^2) cm.cm03=(sum((y-ymean).^3.*A))/(m.m00^2.5) cm.cm11=(sum((x-xmean).*(y-ymean).*A))/(m.m00^2) cm.cm12=(sum((x-xmean).*(y-ymean).^2.*A))/(m.m00^2.5) cm.cm20=(sum((x-xmean).^2.*A))/(m.m00^2) cm.cm21=(sum((x-xmean).^2.*(y-ymean).*A))/(m.m00^2.5) cm.cm30=(sum((x-xmean).^3.*A))/(m.m00^2.5) im(1)=cm.cm20+cm.cm02 im(2)=(cm.cm20-cm.cm02)^2+4*cm.cm11^2 im(3)=(cm.cm30-3*cm.cm12)^2+(3*cm.cm21-cm.cm03)^2 im(4)=(cm.cm30+cm.cm12)^2+(cm.cm21+cm.cm03)^2 im(5)=(cm.cm30-3*cm.cm12)*(cm.cm30+cm.cm12)... *((cm.cm30+cm.cm12)^2-3*(cm.cm21+cm.cm03)^2)... +(3*cm.cm21-cm.cm03)*(cm.cm21+cm.cm03)... +(3*(cm.cm30+cm.cm12)^2-(cm.cm21+cm.cm03)^2) im(6)=(cm.cm20-cm.cm02)*((cm.cm30+cm.cm12)^2-(cm.cm21+cm.cm03)^2)... +4*cm.cm11*(cm.cm30+cm.cm12)*(cm.cm21+cm.cm03) im(7)=(3*cm.cm21-cm.cm03)*(cm.cm30+cm.cm12)... *((cm.cm30+cm.cm12)^2-3*(cm.cm21+cm.cm03)^2)... +(3*cm.cm12-cm.cm30)*(cm.cm21+cm.cm03)... *()

多轴车辆全轮转向转向中心位置，转角比例以及最优控制反馈矩阵求法。(All-wheel steering)

联合对角化，对信号进行预处理，处理信号，作为信号分离的预处理(Joint diagonalization of the signal preprocessing, signal processing, signal separation as pre)

NW_net small world 小世界网络，运行无错误，推荐下载！(NW_net small world of small-world networks, error-free operation, it is recommended to download!)

该算法是以粒子群中粒子的收敛特性为基础,依据量子物理理论提出的,改变了传统粒子群算法的搜索策略,可使粒子在整个可行解空间中搜索寻求全局最优解。同时该算法的进化方程中不需要速度向量,而且进化方程的形式更简单,参数较少且容易控制。对两个算例进行仿真测试,证实该算法可有效解决经济负荷分配问题 性能对比显示,该算法求得的解优于已有的改进粒子群算法及其它优化算法所求得的解。(The algorithm is based on convergence particle swarm particle basis, according to the theory of quantum physics, particle swarm algorithm has changed the traditional search strategies, allow the particles throughout the feasible solution space search seek the global optimal solution. Meanwhile, the algorithm does not need velocity vector evolution equations, and evolution equations simpler and less parameters and easy to control. Two examples of simulation tests confirmed that the algorithm can effectively solve the economic load allocation performance comparison shows that the algorithm is superior to existing solutions obtained improved PSO algorithm and other optimization algorithms obtained solution.)