matlab遗传算法

说明：  CA算法可以将数量型属性划分成若干个优化的区间，它综合了分层聚类于划分聚类的优点，对于给定的不同的初始类个数，CA算法能随着迭代过程的不断进展改变类的数目，一些竞争力差的类即类的基数小于给定阙值的类将在迭代过程中不断消失，最终得到能够有效体现数据实际分布情况的优化聚类个数。(CA algorithm for quantitative attributes can be divided into a number of the interval optimization, hierarchical clustering which combines the advantages of clustering in the division, for a given number of different types of initial, CA algorithm as the iterative process the continuous progress of change in the number of categories, some categories of poor competitiveness of the base type that is less than the value of a given category Que iterative process will continue to disappear and eventually be able to effectively reflect the actual distribution of data to optimize the number of clustering.)

声源定位中，提高时延估计精度的一种方法，即通过将原始信号取其立方后在做相关，得到的峰值更加尖锐。(Sound localization, the increase in the accuracy of time delay estimation method, whichever is the original signal through the cube after doing related to the peak obtained is more acute.)

说明：  有限元结构计算中，梁单元两节点（12自由度）的全局坐标系-局部坐标系转换(Global coordinate system to local coordinate system transformation of two nodes (12 degrees of freedom) of beam element in finite element structural calculation)

Guassian apodized fiber bragg grating

matlab图形界面设计总结，希望对大家有所帮助(matlab GUI design summary, we want to help)

通过 MIMOsimSpectralHelp() 输入不同参数，可以模拟和比较在不同结构和环境下MIMO系统的性能；有助于我们理解MIMO。(Enter through MIMOsimSpectralHelp () with different parameters, you can simulate and compare the performance of different structures and environments in MIMO systems help us understand MIMO.)

pusrsuing my doctorate in mechanical engineering at present doing in finite element methods

These files gives information of unified power flow control

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.)

Matlab 7.0 安装的详细教程(Matlab installation detailed tutorial)