ka-e-man-lv-bo

科学计算和工程中常会产生大量的离散数据，提供绘制这些数据并以图形的形式显示出来。(允许输入拉丁字符的拼音 请键入文字或网站地址，或者上传文档。 取消 Kēxué jìsuàn hé gōngchéng zhōng chánghuì chǎnshēng dàliàng de lísàn shùjù, tígōng huìzhì zhèxiē shùjù bìng yǐ túxíng de xíngshì xiǎnshì chūlái.将中文译成英语Central Standing Committee of scientific and engineering calculations produce a large number of discrete data, mapping data and provides graphical form displayed. )

在语音信号处理中，特征的聚类用matlab来实现(in voice signal processing, feature clustering to achieve using Matlab)

自己写的求解网络最大流问题的Ford-Fulkerson迭代算法MATLAB实现代码(MATLAB code of Ford-Fulkerson algorithm for solving max flow problem in network)

matlab for communication

说明：  数据太多，复制粘贴麻烦，将多个数据文件合成一个文数据文件，(so much data ,it s trouble that use copy and past function. So make progran make more files synthesis one file )

Texture Similarity Measurement

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)

可以很好地分析信号的包络谱，效果非常的明显，并且已经在matlab上成功运行(Is a good way to analysis the spectral envelope of signal, effect is very obvious, and it has been successfully run in matlab )

16 qam simulation using mathlab to carry out

讲述最优化问题，matlab优化工具箱，matlab编程，侧重于优化算法的matlab实现(About the optimization problem, matlab optimization toolbox, matlab programming, focusing on the optimization algorithm matlab implementation)