巴克码 barker code

深度有向寻圈。访问当前某个顶点的后继，再访问后继的某个子顶点，若没有，返回上一层访问其他后继(Depth of the search circle. The current follow-up visit to a vertex, then visit a subsequent sub-vertex, if not, return to the level of other follow-up visit)

蚁群算法三维路径规划 蚁群算法蚁群算法路径规划(RRT fast random spanning tree algorithm for sorting contain four different versions of the code has been collated all the available version 4 codes are matlab)

一种广义预测控制实例，内涵几个m文件，以及说明(An Example of Generalized Predictive Control)

说明：  层次分析法计算权重，判断矩阵一致性检验的Matlab源程序代码(Analytic Hierarchy Process (AHP) calculates weight and judges Matlab source code for matrix consistency checking)

用matlab编程，rbf神经网络进行负荷预测的程序(Using matlab programming, rbf neural network load forecasting procedures)

IHS变换域的遥感图像NSCT融合算法 石爱业 马艳军 黄凤辰 徐立中 河海大学学报(自然科学版) 2008-11-25 期刊(NSCT ihs transform domain of remote sensing image fusion algorithm stone love industry Ma Yanjun Huang Fengchen Xu Lizhong journal of hohai university (natural science edition) 2008-11-25 journals)

Web Hotel Using Solaris Containers

AdaBoost元算法属于boosting系统融合方法中最流行的一种，说白了就是一种串行训练并且最后加权累加的系统融合方法。 具体的流程是：每一个训练样例都赋予相同的权重，并且权重满足归一化，经过第一个分类器分类之后， 计算第一个分类器的权重alpha值，并且更新每一个训练样例的权重，然后再进行第二个分类器的训练，相同的方法....... 直到错误率为0或者达到指定的训练轮数，其中最后预测的标签计算是各系统*alpha的加权和，然后sign（预测值）。 可以看出，训练流程是串行的，并且训练样例的权重是一直在变化的，分错的样本的权重不断加大，正确的样本的权重不断减小。 AdaBoost元算法是boosting中流行的一种，还有其他的系统融合的方法，比如bagging方法以及随机森林。 对于非均衡样本的处理，一般可以通过欠抽样(undersampling)或者过抽样(oversampling)，欠抽样是削减样本的数目， 过抽样是重复的选取某些样本，最好的方法是两种进行结合的方法。 同时可以通过删除离决策边界比较远的样例。 (AdaBoost boosting systems dollar fusion algorithm is the most popular one, it plainly systems integration approach is a serial train and final weighted cumulative. Specific process is: Each training example is given equal weight, and the weights satisfy normalization, after the first classifiers after Calculating a first classifier weights alpha value for each sample and updates right weight training, and then the second classifier training, the same way ....... 0, or until the specified error rate training rounds, wherein the label is the calculation of the final prediction system* alpha weighted and then sign (predicted value). As can be seen, the training process is serial, and weight training examples is always changing, the right of the wrong sample weight continued to increase, the right to correct sample weight decreasing. AdaBoost algorithm is an element, as well as other methods of boosting popular systems integration, such as bagging and random forest method. For )

异步电机MATLAB仿真程序，大家可以多多交流。。。。(Induction motor MATLAB simulation program, we can interact. . . .)

mATLAB cov函数详细说明 很棒，很好(mATLAB cov function details)