FFF12

introduction to optimization是一本介绍优化方法的很好的书籍，对各个行业的优化编写、MATLAB程序编写、或者优化入门具有重要的指导价值，建议通读。(introduction to optimization is a very good book describes optimization methods to optimize the preparation of various industries, MATLAB programming, or optimize entry has important guiding values ​ ​ recommended read.)

Player/stage program about slam

《Matlab遗传算法工具箱及应用》这本书附带的的源码( Matlab genetic algorithm toolbox and its application, attached to this book s source code)

it is cluster1 matlab code

通过遗产算法计算函数最小值的MATLAB程序代码。GA GP (Heritage minimum of MATLAB program algorithm)

psuedo noise code in matlap

用matlab制作的模拟动画程序，内容为电梯的升降演示。(Animation produced using matlab simulation program, the content of the elevator lift demonstration.)

The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order (The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order)

matlab labs that will be very good for the beginners at least. Also, we can use this to promote our skills with matlab use.

高斯消元法MATLAB实现，小报告形式展现(Gaussian elimination MATLAB implementation)