gauss_seidel

说明：  此为MATLAB写的关于2DPSK调制解调的程序并且通过验证可以实现，程序对2DPSK的算法都有相应的程序(This is written in MATLAB on 2DPSK modem to verify the procedure can be achieved through the procedures of the algorithm 2DPSK procedures have corresponding)

包括欧拉梁单元，杆件梁单元，Truss单元，边界处理等。可通用，里面有变量说明。详细可参考THE FINITE ELEMENT METHOD USING MATLAB(Euler beam element)

一个完整Matlab程序，实现了粒子群算法与人工鱼群算法的比较，体现了两种算法各自的优缺点(A complete Matlab program to achieve a particle swarm optimization and artificial fish school algorithm, two algorithms reflects the advantages and disadvantages of each)

about matlab image processing toolbox

逆短时傅立叶变换源代码.适合于非稳态的时频联合分析,可直接用于MATLAB编程,无解压密码.(inverse Fourier transform source code. Suited to the non-steady-state joint time-frequency analysis can be used directly in MATLAB programming, without extracting passwords.)

基于最小二乘支持向量机理论,结合某风电场实测风速数据,建立了最小二乘支持向量机风速预测模型。对该风电场的风速进行了提前1h的预测,其预测的平均绝对百分比误差仅为8.55 ,预测效果比较理想。同时将文中的风速预测模型与神经网络理论、支持向量机(support vector machine,SVM)理论建立的风速预测模型进行了比较。仿真结果表明,文中所提模型在预测精度和运算速度上皆优于其他模型。 (Based on least squares support vector machine theory, combined with a wind farm measured wind speed data, the establishment of a wind vector machine forecasting model of least squares support. The velocity of the wind farm were predicted in advance 1h, the mean absolute percentage error of only 8.55 of its forecast, forecast effect is ideal. While the text of the wind speed forecasting models and neural networks, support vector machines (support vector machine, SVM) wind speed prediction models were compared with established theories. Simulation results show that our proposed model on prediction accuracy and computing speed are superior to other models.)

figure of qpsk mod_demod

直驱风电机组matlab/simulink仿真模型,很有用的风电仿真模型(Direct drive wind turbine simulation model matlab)

It is the huffman codage on matlab

用有限差分法来解偏微分方程，采用高斯——赛德尔迭代方法，并用前后两次迭代差的矩阵的无穷范数作为是否停止迭代的依据。(Using finite difference method to solve partial differential equations, using Gauss- Seidel iterative methods, and poor before and after the two iterations of the infinite matrix norm as the basis of whether or not to stop iteration.)