shuyiyuan

先定义允许状态S={(x,y)|x=0或3,y=0,1,2,3 x=y=1,2}, 允许决策D={(u,v)|u+v=1,2},求dk<-D(k=0,1,2,…,n),使 状态Sk<-S按照状态转移律S(k+1)=S(k)+(-1)^k*dk,由初始状态 S1=[3,3]经有限步到达状态S(n+1)=[0,0].此为求解多步决策问题( First define to allow the state S = ((x, y) | x = 0 or 3, y = 0,1,2,3 x = y = 1,2), to allow the decision-making D = ((u, v) | u+ v = 1,2), seek dk < -D (k = 0,1,2, ..., n), so that state Sk < -S state transition in accordance with law S (k+1) = S (k )+ (-1) ^ k* dk, from the initial state S1 = [3,3] by the finite-step to reach the status S (n+1) = [0,0]. This is a multi-step decision-making problem solving)

Maplestory Client version 140+

说明：  预测控制例子代码，可以实现预测控制，有注释，可以根据需要修改(Predictive control example code, which can realize predictive contro)

amica-modified ica algorithm

使用matlab编写的用wolf法求Lyapunov指数的算法程序 假近邻法(False Nearest NeighborFNN)计算嵌入维的Matlab程序 一类基于奇异值分解的Lyapunov指数计算方法(Matlab program using Matlab prepared wolf method and the Lyapunov exponent of the false nearest neighbor algorithm program (False Nearest NeighborFNN) calculation of the embedding dimension, Lyapunov exponent calculation method based on singular value decomposition)

在这里输入需要翻实现parzen 库中找出与当前情况距离最近的样本的方法.把距离定义为相匹配的输入事例的特征加权和译的文字(Enter here the realization of the need to turn parzen library with the current situation to find the nearest sample. Defined as the distance to match the characteristics of the input-weighted case and translated text)

对输入的语音信号进行分帧处理，低通滤波，中心削波，求自相关函数最后得到基音轨迹。(Speech input signal framing processing, low-pass filtering, center clipping, seeking autocorrelation function finally got the pitch trajectory.)

这是采用模糊粗糙集的方法处理图像的matlab代码(This is a fuzzy rough set approach to image matlab code)

混沌时间序列分析版，里面包括了很多的代码，有lyapunov，CC，GP等等计算混沌的算法(Chaos time series analysis, including a lot of code, and CC, GP, lyapunov calculation of chaos)

采用最小二乘逼近作为拟合实验数据的方法,利用F检验,确定实验数据拟合优度及最佳阶数,用编制的程序来拟合实验数据,得到了较好的结果(Least-squares fitting)