random_tour_2opt

偏最小二乘法简化方法，输入合适的数据，即可得到正确的主因子数，及回归方程。(Simplified method of partial least squares, enter the appropriate data, the main factor to get the correct number, and the regression equation.)

TD-LTE 物理层解传输分集预编码matlaB仿真程序(TD-LTE physical layer solution of transmission diversity precoding matlaB simulation program)

这是一个关于模糊TS模型的例子，对初学TS模型的人很有用(This is an example of fuzzy TS model, TS model for beginners who are useful)

对地震剖面图求出某一区域的外源干扰的公式(The seismic cross-sectional view obtained in a region of exogenous interference formula)

ccs网页上图像样式处理。内含有两个文件，一个是样式里包含两个按钮风格。(ccs style image processing.)

（一）目的：通过对常用的概率密度函数和分布函数的应用，达到熟练掌握概率密度函数和分布函数调用方法的目的。 （二）任务：对实际的案例进行分析，调用相应概率密度函数和分布函数，使用MATLAB软件计算其结果。 （三）要求：理解概率密度函数和分布函数，能够解决实际问题。 ((A) Purpose: used by the probability density function and distribution function of the application, to master the probability density function and distribution methods of the purpose of function call. (B) tasks: the actual analysis of the case, call the corresponding probability density function and distribution function, the use of MATLAB software to calculate their results. (C) requirements: understanding of the probability density function and distribution function, to solve practical problems.)

贝叶斯公式在临床中的应用是利用贝叶斯公式根据验前概率和条件概率来推算验后概率, 进而帮助诊断患者到底患种疾病中的哪一种。具体方法是根据以往积累统计资料, 对种疾病的验前概率人及各种条件概率人进行估算。在诸症状的一种具体组合已经出现的条件下, 按贝叶斯公式计算出各种疾病在这种具体症状组合下发生的概率即验后概率。比较各疾病的验后概率。如果某疾病人的验后概率明显大于其它疾病的验后概率, 便可诊断患者患的哪种疾病。(According to mass statistical results, try to work out the probability of 4 diseases and the class-conditional probability()

压缩感知（compressed sensing，cs）在MRI上的应用，该程序生成傅里叶变换域的射线采样模式用作随机测量 (Compressed sensing (compressed sensing, cs) on MRI, the program generates the rays of the Fourier transform domain sampling mode as random measurement)

非常经典的小波信号分解matlab代码，代码思路很清晰，对初学者很有帮助！(Very classic wavelet signal decomposition matlab code, the code is very clear ideas, helpful for beginners!)

说明：  遗传算法实现50维函数优化，代码简单易懂，适合初学者。(Genetic algorithm of 50-dimensional function optimization, code easy-to-read, suitable for beginners.)