PMSM

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.)

调试所用Matlab版本是6.5，gatbx-toolbox是调试过程中使用的工具箱，有些热心的研友已经提供了该工具箱，之所以再贴一遍，是因为6.5版本下调试该工具箱会出现一些错误提示，在该版本中已经进行了改正，使用该工具箱只需要将压缩包下的gatbx和gatbxTest_fns加入到Matlab搜索路径即可，另外gatbx-origin是Sheffield大学提供的原始版本的工具箱，未做任何改动，两者可做比较之用 3.gatbx-example是算例调试源码和各算例的调试说明，大家可以对照原书进行比较 4.窃以为gatbx工具箱较之Matlab7新版下的gads工具箱更能让人熟悉和了解遗传算法的原理和计算过程，虽然在可视化方面不及gads 5.学习遗传算法如果首先用熟相关工具箱的话，能够先培养信心，然后更有兴趣去专研和了解具体的算法，如果就用现有的工具箱就能解决问题的话，不了解其详细的算法也未尝不可，毕竟不是每个研友都能向see_moonlight那样开发自己的工具箱吧, ( The debugging uses the Matlab edition is 6.5, gatbx-toolbox debugs the toolbox which in the process uses, somewhat warm-hearted ground the friend already to provide this toolbox, the reason that pasted again, was because under 6.5 editions debugged this toolbox to be able to present some wrong prompts, had already carried on the correction in this edition, will use this toolbox only to need to compress package of under gatbx and gatbx Test_fns joins to the Matlab search path then, moreover gatbx-origin was the primitive edition toolbox which the Sheffield university provided, has not made any modification, both might make the comparison are the example debugging sound code and various examples debugging explained with 3.gatbx-example, everybody might compare the original bookCarries on comparison 4. in my opinion under the gatbx toolbox s to be able to let the human compared with Matlab7 update gads toolbox be familiar with the understanding genetic algorithm principle and)

numerical code for matlab analytical bisec differentiation F FALSEPOS fixedpoint

Yeah I actually fixed it by moving a bunch of stuff to onResume(). There are also a number of other bugs I found in this code posted here (which was based on even buggier code) that I will post as soon as I get them all fixed. The first one that comes to mind is that in the try block it needs to check if c is null. Another one is that there is no error handling for a source going down midstream

说明：  matlab 编程实现人体跟踪与检测编程实现人体跟踪与检测(matlab)

采用稀疏矩阵的PQ分解法潮流计算程序（依据《电力系统计算》一书附录用C语言编写，使用方法、变量名称都与书上一致）(Decoupled load flow)

实现傅里叶变换，并进行频谱分析其中包括带通子波波形的实现。(The Fourier transform )

windows media format 9 for images(nine windows media format for images)

计算互信息和作庞卡来截面的C程序，很实用，计算速度超快／(Calculation of mutual information and for Ponca to the C-section procedure, it is useful to calculate the speed of ultra-fast /)

说明：  比例导引法的MATLAB，程序，希望大家多侃侃(matlab)