Kalman

利用matlab程序编写可以实现找到曲线标记的方法以及可以指定坐标轴范围的程序。(Matlab programmers can use to find curves labeled realize Ways and axes can specify the scope of procedures.)

系统辨识与自适应控制中----递推增广最小二乘参数估计算法(Augmented recursive least squares parameter estimation)

运用matlab的m文件来求样本的自协方差，自相关函数(Seeking sample autocovariance and autocorrelation function)

DC MOTOR CONTROL PID USING MATLAB and SIMULINK

采用猫映射图像加密，有二维三维到四维。都是已经在matlab运行通过的(Cat mapping using image encryption, there are two-dimensional to three-dimensional four-dimensional)

实现用LMS算法进行自适应滤波的仿真，基于GUI实现(Implementation using LMS algorithm for the simulation of adaptive filter, based on the GUI implementation )

说明：  它主要研究的是多因变量对多自变量的回归建模，特别当各变量内部高度线性相关时，用偏最小二乘回归法更有效。另外，偏最小二乘回归较好地解决了样本个数少于变量个数等问题。 偏最小二乘法是集主成分分析、典型相关分析和多元线性回归分析3种分析方法的优点于一身。它与主成分分析法都试图提取出反映数据变异的最大信息，但主成分分析法只考虑一个自变量矩阵，而偏最小二乘法还有一个“响应”矩阵，因此具有预测功能。(It is mainly a result of the study is a multi-variable regression modeling and more independent variables, especially when the internal height of each variable linear correlation, partial least squares regression method is more effective. In addition, partial least squares regression solves the number of samples is less than the number of variables and other issues. Partial least squares method is a set of principal component analysis, canonical correlation analysis and multiple linear regression analysis of the advantages of the three methods in one. It is the principal component analysis are trying to extract the maximum information reflects data variability, but the principal component analysis considers only one independent variable matrix, and partial least squares and a &quot response&quot matrix, predictive capabilities.)

learning matlab to use it properly

experiments for multimedia lab

fuzzy code algorithm for function approximation