force-optimization-matlab

18664MATLAB7.x入门与实战（程序代码），书籍的随书光盘程序代码，包含书中所有例题程序，非常实用。(18664MATLAB7.x entry and Actual (program code), books, CD with the book code, the book contains all the example program, very useful.)

关于bootstrap的经典文献一篇，这是Introduction to the Practice of Statistics第五版中第14章。(The classic literature on the bootstrap one, which is Introduction to the Practice of Statistics in the fifth edition of Chapter 14.)

DIFFERENT ARTICLES , USEFUL FOR ELECTRICAL ENGINEERING , ECONOMIC DISPATCH

关于LMI的论文 在matlab中实现的(about LMI paper)

Double side band-suppressed carrier (DSB-SC)simulation on simulnik-matlab.

说明：  共轭梯度法（Conjugate Gradient）是介于最速下降法与牛顿法之间的一个方法，它仅需利用一阶导数信息，但克服了最速下降法收敛慢的缺点，又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点，共轭梯度法不仅是解决大型线性方程组最有用的方法之一，也是解大型非线性最优化最有效的算法之一。 在各种优化算法中，共轭梯度法是非常重要的一种。其优点是所需存储量小，具有步收敛性，稳定性高，而且不需要任何外来参数。(The Conjugate Gradient method is a method between the steepest descent method and the Newton method. It only needs to use the first derivative information, but overcomes the shortcomings of the steepest descent method and avoids the need for the Newton method to store And the calculation of Hesse matrix and the inverse of the shortcomings, conjugate gradient method is not only to solve large-scale linear equations one of the most useful methods, but also solution for large-scale nonlinear optimization of one of the most effective algorithm. In a variety of optimization algorithms, conjugate gradient method is a very important one. The advantage is that the required storage capacity is small, with step convergence, high stability, and does not require any external parameters.)

Feature selection using laplicat sours

基于matlab的字母识别，基于模板匹配，因为采用区域生长法，速度可能有些慢！(Base on matlab!)

特征选择方法,matlab实现增 l减 r法 顺序后退法 SFFS 特征选择 顺序前进法特征选择(feature selection)

remote sensing for texture