FEM_COHESIVE_V2

用c++实现的对游程编码的译码以及编码操作。对信息论一块的游程编码的理解具有一定参考价值。(C++ with the realization of run length coding decoding and encoding operation. For information on the run length encoding a piece of understanding has a certain reference value.)

卡尔曼滤波matlab源代码,提供了详细的代码(the .m file provides the detail process of kalman filter,also includes the explanation)

用三种不同的方式在矩形材料内切出指定半径大小的圆的算法，本来是建模实习的作业题(Three different ways in the rectangular-cut material the size of the specified radius of a circle algorithm, it is modeling the operation of internship title)

techniques for solving a single nonlinear equation

说明：  LDPC码的编译码算法的实现与仿真，以及平均误码率的分析。(LDPC code decoding algorithm implementation and simulation, and the average bit error rate analysis.)

采用间接电流控制的双闭环LCL单相并网逆变器仿真(LCL simulation)

说明：  相场模拟晶枝生长，采用有限差分法计算，可更改参数获得不同结果(Phase field simulated dendrite growth)

Matlab based Wireless card (GPRS/WLAN) driver. or optionally a Bluetooth connection to a GPRS modem

adaboost算法的一个简要编程,对于训练算法能有一个很好的初步指导作用(AdaBoost algorithm is a brief program for the training algorithm can have a good initial guide)

说明：  Matlab数据统计和分析的程序，包含下面所列的多种算法的 MultiLineReg 用线性回归法估计一个因变量与多个自变量之间的线性关系 PolyReg 用多项式回归法估计一个因变量与一个自变量之间的多项式关系 CompPoly2Reg 用二次完全式回归法估计一个因变量与两个自变量之间的关系 CollectAnaly 用最短距离算法的系统聚类对样本进行聚类 DistgshAnalysis 用Fisher两类判别法对样本进行分类 MainAnalysis 对样本进行主成分分析(Matlab data and analysis procedures, listed below contain a variety of algorithms MultiLineReg estimated by linear regression of a dependent variable with a number of independent variables of the linear relationship between PolyReg estimation using a polynomial regression with dependent variable a variable relationship between CompPoly2Reg using quadratic polynomial regression method is estimated that fully a dependent variable and the two since the relationship between variables with the shortest distance CollectAnaly hierarchical clustering algorithm for clustering of samples with Fisher two types of DistgshAnalysis discriminant method to classify samples on the samples MainAnalysis principal component analysis)