Scalebox

radar equation in matlab

lms算法对信号进行线性预测，程序非常棒，欢迎借鉴(lms algorithm for linear prediction signal, the program is great, welcome to learn)

此程序为发表过的一篇IEEE PIMRC 的paper的程序代码。是关于异构无线网络环境下的垂直切换接口激活时间的几个方案的仿真性能比较。(This RAR package contains a set of program code which was used in a published paper on in IEEE PIMRC. It is about the interface activition time in heterogeneous wireless networks. )

说明：  matlab 编程（第七版),英文书籍，详细阐述了matlab工具的使用(Timothy A. Davis.MATLAB Primer.7th ed.CRC.2005)

小生境遗传算法在函数优化中应用—自适应小生境递阶遗传算法(Niche Genetic Algorithm in function Optimization- adaptive niche hierarchy genetic algorithm)

example program of non linear equation

说明：  在matlab环境下编写的快速傅里叶变换程序，改变换程序简单有效(Matlab environment in the preparation of the fast Fourier transform procedure to change the procedure for simple and effective)

在这项工作中所使用的方法是基于一个由大卫阿诺德教程。 http://online.redwoods.cc.ca.us/instruct/darnold/diffeq/logistic/logistic.pdf 这将运行该Logistic.m带来了图形用户界面。 1。放弃在列的格式文本文件中的x值 2。放弃在山口格式文本文件中的y值 3。的阴谋初始 按钮将绘制的分布 4。 查找适合 按钮，会找到最适合 5。 重置 将删除的情节（虽然我想打扫所有的领域 -没有时间） 5。地下K，糖尿病在下列公式中的值 Ÿ 等于k/（1+进出口（- G *的（十型录））） 6。上证所给出了squred误差之间的拟合函数与实际数据的总和 7。消委会提供的相关合作关系的实际数据拟合功能和效率(The method used in this work is based on a tutorial by David Arnold. http://online.redwoods.cc.ca.us/instruct/darnold/diffeq/logistic/logistic.pdf RUN The Logistic.m this will bring up the GUI. 1. Give the x values on a text file in column format 2. Give the y values on a text file in col format 3. Plot Initial Button will plot the distribution 4. Find Fit button will find the best fit 5. Reset will remove the plot (Although I wanted to clean all the fields- did not have time) 5. K, G, Dm are the values in the following equation y = K./(1+exp(-G*(x-Dm))) 6. SSE gives the sum of squred error between the fitted function and the actual data 7. CC give the correlation co-efficient between the fitted function and actual data)

Fourier Series and Power Spectrum with MATLAB

广义预测算法MATLAB转化为VC++的程序,可用于三容水箱的数据的采集.(generalized predictive algorithm MATLAB into VC procedures can be used for three-tank of data acquisition.)