PatternRecognition_complete

it is a matlab file used to create figures for digital ofdm process

matlab excel compiled programming

说明：   使用二分法对样本集进行剪辑，剪辑法的思想，就是将样本集分成训练集与考试集， 利用训练集样本对考试集的样本进行分类（使用近邻法），如果考试集中某个样本分类错误的话，将这个样本删除。在该函数中，使用最近邻法，只进行一次剪辑（遍历完考试集中的样本以后退出）。还有一种重复剪辑法（适用于样本比较多的情况），把样本随机分为多个样本集，将相邻的两个样本前一个作为考试集，后一个作为训练集，调用二分剪辑。所有的样本子集剪辑完毕以后，在递归调用，直到没有样本被剪辑掉,没得讲，重复剪辑的效果肯定好一些。 (The sample sets using the dichotomy of the clips, editing law idea is to sample set into training set and test set, using the training set samples to the test set of samples (using the nearest neighbor algorithm), if the examination focused on a sample of classification error then delete this sample. In the function, use the nearest neighbor method, only once clips (focused on a sample of traversal finished after the exit exam). There is also a repeat clip method (samples are more applicable to the case), the samples were randomly divided into multiple sample set, the two adjacent samples of the former one as a test set, the latter one as a training set, call the two sub-clips. All the samples were a subset of the clips after they have finished, in the recursive call, until there are no samples were clip out, did not have to say that the effect of repeated clips definitely better.)

image processing , laplacian filter using matlab

关于MATLAB的ppt资料，简明扼要的讲解了matlab。(MATLAB' s ppt on information concisely explained matlab.)

kICA implementation

fuzzy c-mean code in matlab in brain segmentation

此模块，是SVPWM仿真，山区判断，时间计算，PWM的产生各个部分组成。结果理想，可用于PMSM和PMLSM的控制中。(This module is SVPWM simulation, the sector judge, time calculations, the composition of each part of the PWM generation. Ideal results can be used for the control of PMSM and PMLSM.)

异步电机矢量控制仿真，包含各种基础矢量控制仿真，包含速度环，电流环，励磁环等。(Asynchronous motor vector control simulation, including a variety of basic vector control simulation, including speed loop, current loop, excitation ring, etc.)

智能算法研究的书籍，可以研究粒子群的发展以及其现在的研究状况(Intelligent algorithms book, you can study the development of PSO and its current research status)