videos_in_matlab

说明：  fdtd 例程，了了解和学习FDTD方法的基础，呵呵，很不错的哦(fdtd routines, understanding and learning based on the FDTD method, huh, oh very good)

Algorithm/Flowchart for C

这是一个matlab 太阳能电池的脚本程序(this is a matlab pv battery m-file)

this file is matlab code for hunting search algorithm.i think it can be so useful.thanks

一般情况下，我们都是在MATLAB命令行或DOS命令行下编译MEX程序。 所用的命令就是：mex filename.c 这有很多不方便的地方： a. 虽然mex也可以编译C++的mex程序，但是它的主框架仍是C的 a. 当程序有多个模块时，需要多次使用mex命令，操作很麻烦 b. 不能利用VC特有的ClassWizard自动创建和维护类 c. 不能用MFC类库编写应用程序 d. 不能方便地进行类似VC的项目管理 本文详细解说如何在IDE中编译MEX程序(Under normal circumstances, we are all in the MATLAB command line or DOS command line program to compile MEX. Command is used by: mex filename.c This has a lot of inconvenient places: a. Although the mex can also compile C++ The mex program, but it is still the main frame C of a. When the procedure has a number of modules the need to repeatedly use the mex command, the operation is cumbersome b. Can not use VC-specific ClassWizard automatically create and maintain the category c. can not use MFC class library to write applications easily d. should not conduct a similar project management VC a detailed explanation of how this article IDE compiling MEX procedures)

this file gives the parameters of a model estimated from given data. this is usfull in estimationa and forecasting

《MATLAB神经网络30个案例分析》中的第一个例子，案例1 BP神经网络的数据分类-语音特征信号分类。希望对大家有用！ (" MATLAB neural network 30 case studies" in the first example, case 1 BP neural network data classification- speech feature signal classification. I hope useful!)

matlab，时间序列分析，分类，数据挖掘，聚类(time series classification)

Image segmentation using watersheds using matlab

曲线拟合法：本方法分别利用一元线性函数、对数函数、指数函数和抛物线函数对数据拟合，取拟合优度判定系数最大者作为预测模型，得出预测值及预测区间（置信度为0.95）(Curve fitting: This method is the use of a linear function, respectively, logarithmic, exponential and parabolic functions for data fitting, goodness of fit to take the maximum coefficient of determination, as predicted by the model, predicted values ??and prediction intervals obtained (confidence 0.95))