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粒子群优化算法(PSO)是一种进化计算技术(evolutionary computation)，有Eberhart博士和kennedy博士发明。源于对鸟群捕食的行为研究 PSO同遗传算法类似，是一种基于叠代的优化工具。系统初始化为一组随机解，通过叠代搜寻最优值。但是并没有遗传算法用的交叉(crossover)以及变异(mutation)。而是粒子在解空间追随最优的粒子进行搜索。详细的步骤以后的章节介绍 同遗传算法比较，PSO的优势在于简单容易实现并且没有许多参数需要调整。目前已广泛应用于函数优化，神经网络训练，模糊系统控制以及其他遗传算法的应用领域(Particle Swarm Optimization (PSO) is an evolutionary computation technique (evolutionary computation), has Dr. Eberhart and Dr. kennedy invention. Deriving from the behavior of birds of prey PSO with genetic algorithm is similar to an iterative optimization-based tools. System initialization for a group of random solutions, through the iterative search for optimal values. But there is no cross-genetic algorithm used (crossover) and mutation (mutation). But the particles in the solution space of the particles to follow the optimal search. In detail the steps after the introduction sections compared with the genetic algorithm, PSO has the advantage of being simple and easy and did not realize many of the parameters need to be adjusted. Has been widely applied to function optimization, neural network training, fuzzy system control, as well as other genetic algorithm applications)

A Power Control Game Based on Outage Probabilities for Multicell Wireless Data Networks

模拟声源在两种介质中产生的声波的传播，采用SPML作为吸收边界(we simulate the propagation of acoustic wave in two media. we use SPML as the boundary conditions.)

演示代码为“独立分量分析:教程介绍”版权:2005年,企业石、心理学系、谢菲尔德大学,谢菲尔德,英格兰。(Demonstration code for "Independent component analysis: A Tutorial Introduction")

koch曲线，分型课程中经常用到的，很好(koch)

Modello pannelli solari in matlab

该CBBA(Consensus-Based Bundle Algorithm)算法可以解决带有任务属性、任务价值、任务时间窗等多种约束下的任务分配问题，结果以图形化展示，便于理解。(CBBA is a decentralized market-based protocol that provides provably good approximate solutions for multi-agent multi-task allocation problems over networks of heterogeneous agents.)

Based on Matlab,Gauss Iteration Method (Based on Matlab, Gauss Iteration Method)

dc motor pwm control in matlab

这个matlab的GUI设计基础教程比较适合初期学习MATLAB的同学(The matlab GUI Design Essentials more suitable for students of early learning MATLAB)