Regulation_dfig

这是一个关于PSO与PID相结合起来的一个程序,其主要用于它的延时用.(This is a study on the combination of PSO with the PID to a process, its main use for its delay.)

主要讲述在matlab环境下的小波变换的工具箱的一系列用法(Focuses on environment in matlab wavelet toolbox of a series of usage)

resource alocation download and enjoy

讨论了LDPC码的基本编码译码原理，然后重点阐述了DVB-S2标准LDPC码的编译码方法。提出了针对DVB-s2标准的LDPC码编 码算法的软件实现 (Paper discusses the basie Principle of LDPC encoding and deocding in the standard of DVB-s2. )

自适应陷波滤波器代码，可以较好地解决信号陷波问题(Adaptive Notch Filter )

matlab经典教材内含习题答案作业答案 源码(An Introduction to Programming and Numerical Methods in MATLAB)

matlab编写的陷波滤波器和维纳滤波器重构模糊图像的程序，还有一个程序实现了冈萨雷斯的《数字图像处理》第5章第20题的问题。(matlab prepared notch filter and Wiener filter blurred image reconstruction process, there is a program to solve the Gonzalez " Digital Image Processing" Chapter 5 of the 20 questions in the question.)

A good Appendix from Wiley Pub Group for understanding Genetic Algorithm you can download from Wiley Web.

An C based HTTP Client. Suitable for Embedded Application Enviroment

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.)