hunxiang

说明：  澳大利亚国防大学的Geoff Mercer博士关于matlab求解微分方程的讲义。重点讲解了初始化、场分析和边界值问题。书中有一些实例，可以结合学习。(Australian National Defense Force Academy, Dr Geoff Mercer notes on matlab to solve differential equations. Highlighting initialization, field analysis and boundary value problems. Some examples of the book, you can combine learning.)

计算机视觉matlab工具箱 里面包含大量计算机视觉的matlab函数(computer vision )

说明：  MLS论文 关于MLs的论文 有推导过程 可以参考(MLS thesis paper on the MLs can refer to a derivation)

foruman baasss en rar

程序1实现了一维Airybeam的三维图形，从x-y面可以看出Airybeam的传输轨迹，三维图形的z轴是光强； 程序2实现了1维Airybeam的轨迹控制，通过改变wm和wg的值可使光强的最大值在任意位置。(A three-dimensional graphics program to achieve a one-dimensional Airybeam the xy plane can be seen Airybeam transfer trajectory, and three-dimensional graphics z-axis is the light intensity 2 implements the program track 1-dimensional Airybeam control, by changing the value of wg wm and the light intensity at an arbitrary position allows the maximum.)

OFDM的详细仿真代码，有信道编码，调制，信道估计等(OFDM detailed simulation codes, channel coding and modulation, channel estimation, etc.)

各程序所完成的具体功能均在文件注释部分中注明！(All procedures are completed in a specific function in the document specified Notes section!)

说明：  MATLAB时频分析工具箱源代码，包括使用说明各种函数库等等(Toolbox MATLAB source code for time-frequency analysis)

编程序给出线性burgers方程解析解 条件：-10<x<10,正三角形位于-0.5 <x <0.5 u和c测试几个数据(Programmed to give a linear analytical solution burgers equation Conditions:-10 <x <10, equilateral triangle at-0.5 <x <0.5 u and c test several data)

粒子群算法，也称粒子群优化算法（Particle Swarm Optimization），缩写为 PSO， 是近年来发展起来的一种新的进化算法(Evolutionary Algorithm - EA)。PSO 算法属于进化算法的一种，和模拟退火算法相似，它也是从随机解出发，通过迭代寻找最优解，它也是通过适应度来评价解的品质，但它比遗传算法规则更为简单，它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作，它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视，并且在解决实际问题中展示了其优越性。粒子群算法是一种并行算法。(Particle swarm optimization, also known as particle swarm optimization (Particle Swarm Optimization), abbreviated as PSO, is a new evolutionary algorithm developed in recent years (Evolutionary Algorithm- EA). Kind, and simulated annealing algorithm PSO algorithm is similar evolutionary algorithms, it is also starting a random solution, through an iterative search for the optimal solution, which is also used to uate the quality through fitness solution, but it is simpler than genetic algorithm rules It has no genetic algorithm " crossover" (Crossover) and " variant" (Mutation) operation, which by following the current search to find the optimal value to the global optimum. This algorithm is its easy implementation, high accuracy, fast convergence, etc. attracted academic attention and show its superiority in solving practical problems. PSO algorithm is a parallel algorithm.)