integrator

建立了风电场模型，并采用模糊前馈的方法进行功率控制(Fan control model, the simulation results)

event management is very important.

Tennesse-Eastman process control system (TE-PCS) simulink

机械测试信号处理 附书的matlab源码。(Mechanical testing signal processing matlab source attached to the book.)

高速跳频，调制样式为DPSK(DPSK/FH)，包括信号的发射接收模型，自己写的代码，仅供参考。(High-speed frequency hopping, modulation pattern for DPSK (DPSK/FH), including the launch of signal reception model, write your own code, for reference purposes only.)

手工指定节点的编号以及位置之后，可以自动生成节点的坐标，以及杆的左右节点，不需要手动输入。(make the topology of truss)

Gaussian映射的分岔图，非线性动力学，MATLAB(Gaussian map bifurcation, Nonlinear dynamics, MATLAB)

产生一个RGB立方图：R(红)-G（绿），R（红）-B（蓝），G（绿）-B（蓝）(Color model. Use Matlab to create six (6) color images of size 512×512 in ppm format, each of which represents one of the six sides of the RGB color cube.)

Field of Digital Communications. Topic: Diversity Combining Matlab Program (m File) for exploiting Receiver Antenna Diversity: Maximal Ration Combining (MRC)

.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.)