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程序控制编程实例24 如何设计多层嵌套异常捕获错误(Programming examples of process control 24 how to design multi-layer nested Exception Catching errors)

ami ，hdb3码的编解码过程，这是在matlab中实现的，但是对我们的编程也很有用处(ami, hdb3 code encoding and decoding process, which is implemented in matlab, but may also be useful to our programming)

围绕粒子群的当前质心对粒子群重新初始化.这样，每个粒子在随后的迭代中将在新的位置带着粒子在上次搜索中获得的“运动惯性”（wvi）向Pi，Pg的方向前进，从而可以在粒子群的运动过程中获得新的位置，增加求得更优解的机会.随着迭代的继续，经过变异的粒子群又将趋向于同一点，当粒子群收敛到一定程度时又进行下一次变异，如此反复，直到迭代结束.(particle swarm around the center of mass of the current PSO reinitialization. Thus, Each particle in the next iteration will be in the new location with particles in the last search was the "inertia" (wvi ) Pi, Pg orientation, and thus can PSO course of the campaign was a new position, increase seek better solutions opportunities. With the continued iteration, after variation of PSO will tend to the same point. When PSO converge to a certain extent when the next variation, so repeatedly, until the end of iteration.)

一个典型的MATLAB河VC++的混合编程，对刚刚起步学习的人很有帮助(a typical VC MATLAB River mixed programming, which has just started to learn the helpful)

Serial port communication for kwp 2000 fast initialization. this code is not complete. I am trying to develop it

在偏微分方程的数值求解中，有一类很重要的问题就是求解有奇异点的泊松方程，此程序是用C写的并行程序，能极大的提高泊松方程的求解(In the numerical solution of partial differential equations, there is a class of very important issues that have a singular point of solving the Poisson equation, this program is written in C parallel programs, can greatly improve the solution of the Poisson equation)

高阶谱分析工具箱，有常见的参数模模型高阶谱估计，DOA估计与时延估计 (Higher order spectral analysis toolbox, common parameter-mode model of higher order spectral estimation of DOA estimation and delay estimation)

网上下载的一个程序开发的示例程序，很实用(Download an example of a program development process, it is practical)

系统模型辨识中使用维纳滤波器，并对SDA,LMS和RLS算法作比较(system modeling realization using winner filtering ,steepest descend alogrithm,LMS algorithm,RLS algorithm)

遗传算法，用matlab来实现，图像美观，更接近真实数据(Genetic algorithm, using matlab to achieve, beautiful images, closer to the real data)