PDE-solution

matlab常见的算法，很有用的，里面有很多的算法，工程人员很有用。(matlab common algorithm, very useful, there are many algorithms, engineers useful.)

说明：  用于特征降维，特征融合，相关分析等多元数据分析的鉴别型典型相关分析（DCCA）Matlab代码实现。(For feature reduction, feature fusion, multivariate data analysis and correlation analysis based identification of canonical correlation analysis (DCCA) Matlab code implementation.)

说明：  振动烈度计算的MATLAB算法，根据振动加速度信号的频域积分计算振动烈度(The MATLAB algorithm for calculating vibration intensity, vibration acceleration signals according to frequency domain integral calculation of vibration severity)

9节点前推回代法潮流计算，基本潮流！源程序(9 nodes forward and backward substitution method flow calculation, the basic trend! Source)

BP神经网络的改进应用Improved BP neural network(Improved BP neural network)

program for crossrelation

反射系数与地震子波褶积合成地震记录，p，d，s分别是预设地层纵波速度、密度、及横波速度模型。其中包含可以改变主频的ricker子波，avopp是提取反射系数的程序。wigb可以对其中的多道进行强化显示。(Reflection coefficient and the convolution synthetic seismogram, the seismic wavelet p, d, s are preset formation p-wave velocity, density, and shear wave velocity model. Contains can change the frequency of the ricker wavelet, avopp is the process of the extraction of reflection coefficients. Wigb can to strengthen the multi-channel display.)

运用PQ控制环节，实现有功功率和无功功率的解耦，通过电流环的跟踪控制环节实现电流的跟踪，通过功率控制环节实现功率因数为1，综上的控制实现光伏三相并网，实现最大效率的能源应用(Using PQ control link to achieve active power and reactive power decoupling to achieve the current track by track control link current loop power control link through to achieve a power factor of 1, the control sum of the three-phase grid-connected photovoltaic achieve, achieve the maximum efficiency of energy use)

A surface chartHAODE曲面画法(A surface chartHAODE)

The aim of this paper is to describe a novel and completely automated technique for carotid artery (CA) recognition, far (distal) wall segmentation, and intima–media thickness (IMT) measurement, which is a strong clinical tool for risk assessment for cardiovascular diseases. The architecture of completely automated multiresolution edge snapper (CAMES) consists of the following two stages: 1) automated CA recognition based on a combination of scale–space and statistical classification in a multiresolution framework and 2) automated segmentation of lumen–intima