FNRCGH

嵌入数字水印~绝对可以实现的，基于DCT变换的，matlab源码 (embedded digital watermark ~ certainly achievable, based on the DCT, Matlab FOSS)

说明：  《Matlab与通信仿真》--信道编码篇--分析循环码的性能（信道任选，调制采用2FSK）(&quot Matlab simulation and communication&quot - Channel Coding Part- 6. Analysis of the performance of cyclic code (optional channel, modulation used 2FSK))

阶跃响应曲线下的bp神经网络的系统辨识，效果良好，能很好的辨识系统。(Bp step response curve of the neural network system identification, good results can be a good identification system.)

说明：  MATLAB语言常用算法程序集。第6章 矩阵特征值计算(MATLAB language commonly used algorithm for assembly. Chapter 6 matrix eigenvalue calculation)

说明：  Radon变换的matlab工具包，大家可以看看(radon&matlab)

运用LBM解得一个浓度方程的小程序，非常有用！解对流扩散方程，可以直接带入自己的！(Use LBM of or concentration of a small program, very useful!Convection diffusion equation, the solution can be directly into your own!)

一些常被用于教学或者参考的概率论的实例的源代码，在Matlab中运行调试(Often used in teaching or some reference examples of the probability of the source code, in Matlab run debug)

将一个m文件转成c /cpp文件并在VC中进行编译。这种方法有个烦人的地方，每次你都需要把matlab生成的一 大堆c和h文件考到vc中，比如我读入一副图片先做膨胀，再腐蚀，再进行小波变换，最后 显示。这样一个程序会生成大概150多个文件，每次都要拷贝这些文件很不方便。我试着用 了另外一种方法，可以简化这些工作。那就是不生成cpp文件交给VC去编译，而是直接在m atlab中生成一个dll交给VC去链接即可。这样无论matlab生成多少文件，都只需要拷贝三 个文件即可。 (m to a document conversion c/cpp files and compile VC. Such a method is a nagging place every time you need Matlab has generated a lot of c and h vc document examination, for example, I read a photo, first expansion, and corrosion, further wavelet transform, the last show. Such a procedure will probably generate more than 150 documents, each copy of these documents must be very inconvenient. I tried another kind of approach can simplify their work. It is not generating cpp documents to the VC to compile, but m atlab directly in the formation of a dll to the VC to link. No matter how many documents generated Matlab, only three need to copy documents.)

fit_ML_rayleigh - Maximum Likelihood fit of the rayleigh distribution of i.i.d. samples!. Given the samples of a rayleigh distribution, the PDF parameter is found fits data to the probability of the form: p(r)=r*exp(-r^2/(2*s))/s with parameter: s format: result = fit_ML_rayleigh( x,hAx ) input: x - vector, samples with rayleigh distribution to be parameterized hAx - handle of an axis, on which the fitted distribution is plotted if h is given empty, a figure is created. output: result - structure with the fields s - fitted parameter CRB - Cram?r-Rao Bound for the estimator value RMS - RMS error of the estimation type- ML

电磁射线理论的经典教材，通信信道仿真必备(Classic textbook theory of electromagnetic radiation, an essential communication channel simulation)