slm

leader-follower聚类算法的matlab实现(leader-follower clustering algorithm matlab realize)

一个黄金分割法,可以运行，不过只是最终结果，想要中间过程就得自己想办法了，我也不会了。两个二分法可以(A golden section method, you can run, but only the final result, like the middle of the process would have their own ways, and I will not. 2 dichotomy can be)

计算泊松方程的方程程序算法。计算物理的非常经典的算法之一。(An algorithm for calculating the Poisson equation. One of the very classic algorithms for computing physics)

说明：  MATLAB的jsp和K聚类算法，试试看，不错的，谢谢(MATLAB' s jsp and K clustering algorithm, give it a try, yes, thank you)

说明：  IS95前向链路系统，MATLAB程序，可直接执行，程序有英文解释，是一个很好的资料

用systerm generation完成BPSK的调制解调过程，这里原理简单易懂，程序来自一本日本书。(Systerm generation with the completion of the BPSK modulation and demodulation process, here the principle of easy-to-read, the program comes from a Japanese book.)

可以实现wstring与string之间的相互转化，同时也包括了string与CString之间的转换(Can achieve mutual conversion between wstring and string, but also includes the conversion between string and CString)

pharse verb get .........................................

基于matlabde的利用互信息的图像的配准(The use of mutual information based matlabde the image registration)

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.)