完美的局部均值分解（LMD）算法，matlab编写

基于matlab的最优控制计算方法及其在超声治疗方面的应用(computional methods for optimal control in ultrasound therapy)

较为详细的介绍倒谱法，传统倒谱法以及对倒谱法的改进算法，以及对倒谱法进行MATLAB实验(A detailed introduction of cepstrum method, the traditional cepstrum method, and the cepstrum method of improved algorithm, and MATLAB experiments of cepstrum method)

hdd compartition fixer rar. Used to fiz partitions

实现高斯背景建模，并且提取运动目标。具有良好的适用性(Gaussian background modeling to achieve, and extract the moving target. Good applicability)

直流微网继电保护策略实现S-function的M文件，主保护为母线直流差动保护，基于小波分解的高频故障电流保护，后备保护为过电流保护，针对系统为2进2出的微网，只需将电流值输入，其中第一个输入变量为开关，为保护算法控制开始/关闭。(The relay protection strategy of DC microgrid realizes the M file of S-function. The main protection is busbar DC differential protection. The high frequency fault current protection based on wavelet decomposition and the backup protection is overcurrent protection. For the microgrid with 2 in and 2 out of the system, only the current value is input. The first input variable is switch, which starts/closes for the control of the protection algorithm.)

The channel modeling work package WP1 of IST-WINNER project provided a Matlab implementation of the WINNER Phase II Model (referred as WIM this onward). The main purpose of the WIM channel models is to generate a radio channel realisations for a link and system level simulations. The implementation is based on the earlier implementations of WINNER II interim model [6], WINNER I (interim) model [3], 3GPP/3GPP2 Spatial Channel Model (SCM) [4] and SCM(E) Extension models. For details concerning the WIM model, please refer to [1]. This document describes the SW implementation structure of WIM, its input/output interface and its functionality. Channel model scenarios and parameters are modified to correspond to IMT.EVAL [7] channel model.

非线性光纤光学中用来仿真二阶色散、三阶色散以及SPM的程序，对刚开始进行科研的人有很大帮助。(Fiber optics used for simulation of nonlinear second-order dispersion, third-order dispersion and SPM process right to conduct scientific research in the beginning there is a great help.)

face database for face recognition

Basically template match with rotation. Given a template as binary edge image the function find the object that match the template in the image. This work even if the template and object are in different orientations. The matching is is done by rotating the template and matching it to the image in various of angles, the best match is returned. Matching the template to the image can be done by various of template match approaches including crosscorrelation and generalized hough transform. See the readme file supplied in the code zip file for more details

说明：  粒子群算法（PSO）是一种基于群体的随机优化技术。与其它基于群体的进化算法相比，它们均初始化为一组随机解，通过迭代搜寻最优解。不同的是：进化计算遵循适者生存原则，而PSO模拟社会。将每个可能产生的解表述为群中的一个微粒，每个微粒都具有自己的位置向量和速度向量，以及一个由目标函数决定的适应度。所有微粒在搜索空间中以一定速度飞行，通过追随当前搜索到的最优值来寻找全局最优值。 PSO模拟社会采用了以下三条简单规则对粒子个体进行操作：①飞离最近的个体，以避免碰撞。②飞向目标。③飞向群体的中心。这是粒子群算法的基本概念之一。 粒子群算法其基本思想是受许多鸟类的群体行为进行建模与仿真研究结果的启发(Particle swarm optimization (PSO) is a population based stochastic optimization techniques. Based on evolutionary algorithms compared with other groups, they are initialized to a random solution, iterative search through optimal solution. The difference is: the principle of survival of the fittest evolutionary computation to follow, while PSO simulation community. The potential of each solution expressed as a group of particles, each particle has its own position vector and the velocity vector, and a fitness determined by the objective function. All particles in the search space at a constant speed flight, by following the current search to find the optimal values ​ ​ of the global optimum. PSO simulation community has adopted the following three simple rules for the operation of individual particles: ① recently departed individuals, in order to avoid collisions. ② to the target. ③ fly to center groups. This is one of the basic concepts of particle swarm algorithm. PSO algori)