gp

sweb a pedestrian MATLAB web session starter

带算例的弧长法,可以对弧长法的运算模式有更加清晰的认识(arc-length with a verification examples)

SIMULINK功能模块的处理SIMULINK功能模块的介绍SIMULINK功能模块的连接(Simulation module processing module SIMULINK introductory SIMULI NK functional modules link)

Image denoising by wavelet analysis

对于声矢量圆阵，比较固定对角加载法（FDL）、加权向量范数约束法（NCCB）两种算法输出信干噪比随快拍数变化。(For acoustic vector circular array, relatively fixed diagonal loading method (FDL), weighted vector norm constraint method (NCCB) two algorithms output SINR with snapshots change.)

只要给出一个二维区域的水平集方程,就可以生成该二维区域的三角形CVT网格。(As long as the region is given a two-dimensional level set equation, we can generate the two-dimensional triangular region CVT grid.)

MATLAB 实验教程，说明！以及手把手的交给你！

一个回转导杆机构的matlab仿真代码，包括其运动仿真，以及变量变化曲线图的生成。(A rotary guide agencies matlab simulation code, including its motion simulation, and variable changes in graph generation.)

This example is based on the integration of interactive simulation environment simulink to do, mainly based on simulink modeling equations, gives the spring mass damper system. We hope to learn about simulink help.

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(（Evolu2tionary Algorithm - EA）。PSO 算法属于进化算法的一种，和遗传算法相似，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。(Particle swarm optimization, also known as particle swarm optimization (Particle Swarm Optimization), abbreviated as PSO, is a new evolutionary algorithm developed in recent years ((Evolu2tionary Algorithm- EA) .PSO algorithm is an evolutionary algorithm, and similar genetic algorithm, it is also starting random solutions, through iterative search for the optimal solution, which is also uated by the quality of the fitness solution, but it is much simpler than genetic algorithms rule, it does not have the genetic algorithm cross (Crossover) and variant (Mutation) operation, which by following the current search to find the optimal value to the global optimum. the algorithm for its easy implementation, high accuracy, and fast convergence advantages attracted academic attention, and in solving practical problems demonstrated its superiority.)