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Penny Shape case Smatrix for Eshelby Function in MicroMechanics

也试着把《MATLAB在振动信号处理中的应用》中的ZFFT改为函数，方便其它坛友的调用，并提供调试程序和数据(Also tried to " MATLAB in Vibration Signal Processing" ZFFT change in function to facilitate the other Friends of the altar call, and debug programs and data)

little matlab script but still no error

in this discussion is about the electrical technology how it is changing day by day

控制弹道程序，关于航行器弹道的控制程序，进行定深航行的仿真程序(The program of trajectory)

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.)

单基地MIMO雷达的DOA估计，使用的是MUSIC算法，并且和CRB进行了对比，生成图片(Monostatic MIMO radar DOA estimation using MUSIC algorithm, and were compared and CRB generated image)

Is a group of GUI files (MATLAB), this permit load and save differents mathematical functions and plots this

Petri网: 基本概念和分析方法 ，对学习perti网仿真和很有帮助(Petri nets: basic concepts and analytical methods, simulation and helpful to learn perti Network)

Trigonometric functions using MATLAB to achieve power spectral analysis