temp_match_fn

这篇经典文章Exact Matrix Completion via Convex Optimization的源代码(This classic article Exact Matrix Completion via Convex Optimization of the source code)

说明：  Matlab课件，简单实用，对于写论文和做仿真的同学很有用(Matlab)

关于目标追踪的一个源代码，比较了卡尔曼滤波和粒子子滤波的跟踪效果。 ，经测试可直接使用。 (A source code on the target track, and compare the tracking performance of the Kalman filter and particle sub-filter. Has been tested and can be used directly.)

Differential of Functions like Sin , Cos , Tan , Cot and other Functions with Central Oh4 method and calculation of errors Differential with matlab program. Saman Darvish

using matlab for create interfce

使用matlab实现信号发生器以及电子琴(A basic signal generator &digital piano based on Matlab)

在Matlab中编写了有向图算法的调用函数(The calling function of directed graph algorithm is written in Matlab)

是一个关于正交匹配（omp）算法实现的程序(Is a match on the orthogonal (omp) algorithm procedure)

说明：  比较全面的MATLAB编程教案，共十四个PPT涵盖MATLAB编程各方面。(MATLAB programming more comprehensive lesson plans, a total of fourteen PPT covers all aspects of MATLAB programming.)

Rosenbrock函数优化属于无约束函数优化问题，其全局极小值位于一条平滑而狭长的抛物线形状的山谷底部，且为优化算法提供的信息很少，因此找到其全局极小值就显得很困难。根据Rosenbrock函数的这种特性，专门提出了一种改进的PSO算法，该算法引入三角函数因子，利用三角函数具有的周期振荡性，使每个粒子获得较强的振荡性，扩大每个粒子的搜索空间，引导粒子向全局极小值附近靠近，避免算法过早地收敛，陷入局部最优，从而找到Rosenbrock函数的全局极小值。大量实验结果表明，该算法具有很好的优化性能，为某些领域某些特定的类似于Rosenbrock函数的优化问题提供了一种新的思路。(Rosenbrock function optimization functions are unconstrained optimization problems, its global minimum value at a smooth parabolic shape and narrow mountain valley Department, and for the optimization algorithm provides little information, and therefore find its global minimum value becomes very difficult. According to this feature Rosenbrock function, specifically mentioning Out an improved PSO algorithm (PSO-R), the algorithm introduced trigonometric factor, using trigonometric has periodic oscillations, so that each particle to obtain more Strong oscillations of expanding the search space of each particle, the particle is close to nearby guide global minimum, avoiding premature convergence algorithm, into a local optimum, thus Finding the global minimum Rosenbrock function. Experimental results show that the algorithm has a good optimizing performance, similar to some certain areas Rosenbrock function in the optimization problem provides a new way of thinking.)