matlabplayer

此程序为matlab的关于辐射增强的一段代码，已经用于开发的软件中(This procedure matlab section on the radiation code has been used to develop the software)

属性分类的粒子群算法Particle swarm optimization (pso) algorithm to the classification of the attribute(Particle swarm optimization (pso) algorithm to the classification of the attribute)

求Weighted/Non-weighted贝叶斯k近邻模型的matlab程序，内含具体说明。(seeking Weighted/Non-weighted k neighbors Bayesian model matla b procedures, containing details.)

BOOST MPPT FOR PV SYSTEM

matable下编的一个算法！线性阈值分类器运用AdaBoost算法！(An Algorithm for under matable! The use of linear threshold classifier AdaBoost algorithm!)

无刷直流电机 伺服控制系统仿真 精华,对转向器等方面有用(The brushless DC motor servo control system simulation the essence of the steering gear and other useful)

Xamarin Essentials eBook

关于数字信号处理的MATLAB例程，包括随机信号产生，线性调频Z变换，卷积(MATLAB on digital signal processing routines, including the random signal generation, chirp Z transform, convolution)

DTMF encoder/decoder using Goertzel algorithm and Biquad filtering

.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.)