cointegration-arbitrage

实现RBF神经网络，用MATLAB的M语言开发的(RBF neural network implementation with MATLAB M-language development)

用matlab编写的三维魔方模拟显示，直接运行first.m即可(Three-dimensional cube simulation using matlab display, can be run directly first.m)

Matlab_基于角点信息和透视变换的图像镶嵌，可以看到最后的比较结果。(Based on the corner Matlab_ information and perspective transformation of the image mosaic, we can see the final results of the comparison.)

Systemview是重要的通信系统仿真软件，国外用的很多。这是我做硕士阶段仿真的一些源代码，对通信系统设计开发非常有用，由于没有Systemview这个板块，所以放在这里。这是一个信号平方仿真的Systemview源代码。(Systemview is an important communication system simulation software used in many foreign countries. This is what I do Simulation Master stage some source code, the communication system design and development is very useful. Because no Systemview the plate, so on here. This is a signal of Systemview square simulation source code.)

snake 算法 matlab源码 snake 算法 matlab源码(snake algorithm matlab source code snake algorithm matlab source code)

MATLAB的数值积分工具箱，大家赶快下载来看看，一定不会让你失望(Numerical integration of MATLAB toolbox, we quickly downloaded to see that we will not let you down)

%fm.m %频率调制的Matlab演示程序. %被调信号为m(t)=sin(100t).( fm.m frequency modulation of Matlab demo program. transferred signal m (t) = sin (100t).)

求解了边界层相似方程,利用了RK方法求解边值问题！得到速度和温度分布剖面(The boundary layer similar equation is solved using RungeKuuta method.)

基于!"#$" 的移动通信中多径衰落信道的仿真(Mobile communications based on !" #$" multipath fading channel simulation)

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.)