epsk

Linear algebra problems!

matpowe3.1b2 Open source software, no modified version downloaded from the official website, different matpower may not apply with each other program

一般支持向量机的回归和分类程序，均可以运行(General support vector machine regression and classification procedures can run)

改进的muller算法 当中不用判断 直接考虑了复数根的情况 并包含一个例子(Improved muller algorithm to determine which do not directly take into account the complex situation in the root and contains an example)

Dikin-Algorithmus, mathematische Optimierung

Matlab编写的音乐播放器,里面有说明文档(a music player written with matlab)

数学建模，第十三讲，报童模型课件，相关的一个代码(Mathematical modeling the newsboy model courseware, the code)

说明：  一个朴素贝叶斯的matlab实现算法一个朴素贝叶斯的matlab实现算法(A Naive Bayes algorithm for matlab in a Naive Bayes algorithm matlab)

交流伺服系统中的死区效应分析与补偿分析了逆变器的死区效应产生的原因及其对交流伺服系统控制性能产生的影响,指出死区补偿的关键 在于电流相位的获取,为了克服实际系统中电流零点的模糊性,提出了一种基于两相静止坐标系下的前馈死 区补偿方法. 该方法通过对三相输出电流一个周期内补偿电压进行傅里叶变换,发现仅需补偿1 ,5 ,7 次谐波 分量即可消除死区效应. 仿真和试验结果验证了这种方法的正确性和可行性.(AC servo system analysis and compensation of dead time effect of the inverter dead time effect causes the impact of the control performance of the AC servo system, and pointed out that the dead time compensation, the key lies in the current phase of the acquisition, in order to overcome the practical zero of the current ambiguity of the system is proposed based on the two-phase stationary coordinate system under the feedforward dead-time compensation method. by the offset voltage of the three-phase output current cycle Fourier transform is found only compensation 1, 5, 7 harmonic components to eliminate the dead time effect. simulation and experimental results verify the correctness and feasibility of this approach.)

In theory, this algorithm tends to provide good generalization performance at extremely fast learning speed.(The experimental results based on a few artificial and real benchmark function approximation and classification problems including very large complex applications show that the new algorithm can produce good generalization performance in most cases and can learn thousands of times faster than conventional popular learning algorithms for feedforward neural networks)