lap

matlab主要的函数与命令，适合菜鸟学习。电子书格式是pdf格式(matlab main functions and command)

field oriented control induction motor

.附件结构: gatbx.rar: (1)gatbx-origin.zip; (2)gatbx-toolbox.rar; (3)gatbx-example.rar 2.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,(Annex structure: gatbx.rar: (1) gatbx-origin.zip; (2) gatbx-toolbox.rar; (3) gatbx-Test_fns under the compression package need to be added to Mat. The lab search path can be done, and gatbx-origin is the original version of the toolbox provided by Sheffield University, without any changes, which can be used for comparison. 3. Gatbx-example is the source code of example debugging and the debugging instructions of each example. You can compare it with the original book. 4. It is assumed that the gatbx toolbox is better than the gads toolbox in the new version of MATLAB 7 in familiarizing and understanding the principle and calculation process of genetic algorithm, although it is less visualized than gads.)

这里有一些有关粒子群算法的工具书，希望对大家有帮助(Here are some of the particle swarm optimization tool, we want to help)

dct4 plus tool for infinity users ok by irfan khan

steganalysis characteristic

BP神经外那个罗可以逼近任意函数，此为拟合函数的源代码(BP neural network can approximate any function, the source code for the fitting function)

刘金琨老师作品，机器人控制系统和MATLAB仿真。(Teacher Liu Jinkun works, robot control systems and MATLAB simulation.)

emd程序，可以用于滤波，得到几个IMF分量，滤掉复杂的波从而分析波的特征(emd program, can be used to filter, get a few IMF component, the complex wave filter to analyze the characteristics of wave)

Chapman - Advanced Mathematics and Mechanics Applications Using MATLAB, 3rd Ed - 2003(Chapman- Advanced Mathematics and Mechanics Applications Using MATLAB, 3rd Ed- 2003)