audoiMATLAB

说明：  多项式曲线拟合其中, x, y为已知数据点向量, 分别表示横,纵坐标, m为拟合多项式的次数, 结果返回m次拟合多项式系数, 从高次到低次存放在向量p中. (Polynomial curve fitting where, x, y as the vector of known data points, respectively, horizontal and vertical coordinates, m is the number of polynomial fitting, the results of m-fit polynomial coefficients returned from higher to Low times stored in the vector p,.)

不同坐标系下相同测量点之间的四元数转换矩阵求解，可以此来求解坐标系A到坐标系B之间的转换矩阵(Different coordinates between the same measurement points quaternion transformation matrix solution can be used to solve this coordinate system A to coordinate system transformation matrix between B)

Law s texture measure

Matlab codes for descriptors

对雷达基本概念进行仿真，还包含了GUI部分，是很好的学习程序。

基于MATLAB的近邻法剪辑算法的实验，源代码，及数据分析(Based on the MATLAB nearest-neighbor method clip algorithm experiment, the source code, and data analysis )

Wiley Wooldridge-An Introduction to Multi Agent Systems

利用SVM做回归线性测试。对于大盘指数的有效预测可以从整体上观测股市的变化提供强有力的信息，所以对上证指数的预测很有意义。通过对上证指数从1990.12.20-2009.08.19每日的开盘数进行回归分析，最终拟合的结果是：均方误差MSE=2.35705 e-005，平方相关系数 R=99.9195 。SVM的拟合结果还是比较理想的。(Make use of SVM linear regression testing. For the market index can predict the observed changes in the stock market as a whole to provide a strong information, so it makes sense to predict the Shanghai index. Through the Shanghai Composite Index opened daily from 1990.12.20-2009.08.19 number of regression analysis, the results of the final fit are: mean square error MSE = 2.35705 e-005, the square of the correlation coefficient R = 99.9195 . SVM fitting result is quite satisfactory.)

非常非常经典的地震学巨著，AKI的定量地震学，基本上是地震工作者的入门书籍(Very very classic seismology masterpiece, AKI quantitative seismology, earthquake workers are essentially introductory book)

This code is for a simple channel equalization using the simplest LMS algorithm