IGAzijibiande

天线的仿真程序，给出了天线的各个参数。具有很高的参考价值(Antenna simulation program, given the various parameters of the antenna. Have a high reference value)

极值理论中各种函数及图像的程序。matlab实现。(Extreme Value Theory in a variety of functions and process images. matlab achieve.)

matlab仿真中的（2,1,2）卷积码和维特比译码的码源。(matlab simulation (2,1,2) convolutional code and Viterbi decoding of the code source.)

fast matrix multiplication

example of matlab,optimization method which is used with different model.it will be useful for whom they want to learn Matlab by themselves2

MATLAB振型分解法代码，超级完整，包含地震波文件。(Mode Decomposition Method Code)

WSN localization using Particle Swarm Optimization

说明：  Adaptive MIMOofdm simulink help

说明：  本代码可实现在MATLAB环境下获取随机分布的数(This code can be realized in the MATLAB environment to obtain the probability of paper, to facilitate data analysis and processing)

高速铁路路基沉降是一个复杂的系统过程,涉及不同时期、不同工况,选用单一的预测模型不足以反映路基整体的变形规律.Logistic模型及Verhulst模型的曲线均为S形,可以反映全过程的地基沉降与时间的关系.针对路基填筑期和降水期两个时段利用MATLAB软件编制程序计算模型参数,得到Logistic模型和灰色Verhulst模型,进而求得两者的最优加权组合模型.对比结果表明:在路基填筑期由两者的最优加权组合模型预测得到的结果与实测结果较吻合,拟合精度高于单一模型 而在降水期Verhulst模型的预测值更接近实测值,平均相对误差约为1.75％,拟合精度较高.(High-speed railway subgrade settlement process is a complex system involving different times and in different conditions, the choice of a single forecasting model does not adequately reflect the overall deformation of roadbed. Curve Logistic model and Verhulst models are S-shaped, the whole process can be reflected foundation settlement versus time. against roadbed construction period of two hours and precipitation using MATLAB software programming model parameters, the Logistic model and gray Verhulst model, and then get the optimal model of a weighted combination of the two. comparative results indicate : results and experimental results in the roadbed construction period by the weighted combination of the best of both models predicted than the anastomosis fitting accuracy than a single model precipitation predicted value of Verhulst model closer to the actual value of the average relative error approximately 1.75 fitting accuracy.)