RNN matlab 例程

说明：  matlab函数，很多有用的matlab函数。希望对大家的学习有用。(matlab function, a lot of useful matlab functions. Hope to learn useful.)

说明：  随机共振的一些论文，很有权威，对研究非线性双稳随机共振系统的人很有帮助(Some of the papers stochastic resonance, very authoritative, the study of nonlinear bistable stochastic resonance systems were very helpful)

这是模式分类一书中第五章的LMS(最小均方算法）和Ho-Kashyap算法的matlab代码实现。(This is the pattern classification of a book chapter V LMS (least mean square algorithm) and the Ho-Kashyap algorithm matlab code.)

遗传算法优化最小二乘支持向量机的核函数参数和正则化参数(Optimization of Kernel Function and Regularization Parameters of Least Square Support Vector Machine by Genetic Algorithms)

小功率电源的matlab仿真程序，实现三相电的转换(Low-power power supply matlab simulation program, to achieve three-phase power conversion)

偏微分方程的matlab程序，可作为数值分析等的学习工具。(Partial differential equations matlab program, can be used as numerical analysis , and other learning tools.)

用于车牌识别，个人感觉比较好，大家可以看一下(For license plate recognition, personal feeling better, we can look at)

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 )

说明：  用于计算HURST指数的分形维数的MATLAB小程序，属于经典的。(HURST index used to calculate the fractal dimension of the MATLAB small procedures, are classic.)

说明：  这里是一些代码，与matlab有关，是一些小技巧。(code, and the Matlab is some small skills.)