mang-watermarking

vb連結matlab 在vb裡面可以使用加減、或sin波(vb connect matlab)

有限差分法的Matlab程序（椭圆型方程）,用有限差分法求解矩形域上的Poisson方程(Finite difference method in Matlab (elliptic equations), the finite difference method for solving the Poisson equation on a rectangular domain)

horner2.PDF CE COURS VOUS PERMETTRA D APPRENDRE D AVANTAGE SUR LA MÉ THODE DE HORNER PROGRAMMATION MATLAB

MATLAB中各代码、函数间的参数传值验证代码，有助于理解matlab中的传值概念(MATLAB, the code, the function returns the value of the parameters between the validation code helps to understand the concept of traditional values ​ ​ in matlab)

遗传算法解决最短路径。在matlab中实现计算和结果输出。(The genetic algorithm to solve the shortest path. Calculated and results output in matlab.)

pso for matlab ... enjoy it

the motion vector of the video sequence is analyzed for improving the error detection rate

Smooths a matrix (with/without NaN s) via recursive moving average method and eliminates data gaps. (MOVING_AVERAGE(X,F) smooths the vector data X with a boxcar window of size 2F+1, i.e., by means of averaging each element with the F elements at his right and the F elements at his left. The extreme elements are also averaged but with less data, obviously. Leaving the edges intact. The method is really fast. MOVING_AVERAGE2(X,M,N) smooths the matrix X with a boxcar window of size (2M+1)x(2N+1), i.e., by means of averaging each element with its surrounding elements that fits in the mentioned box centered on it. This one is also really fast. The elements at the edges are averaged too, but the corners are left intact. NANMOVING_AVERAGE(X,F) or NANMOVING_AVERAGE(X,F,1) accept NaN s elements in the vector X the latter interpolates also those NaN s elements surrounded by numeric elements. NANMOVING_AVERAGE2(X,M,N) or NANMOVING_AVERAGE2(X,M,N,1) accept elements NaN s in the matrix X the latter interpolates also those NaN elements surrounded by numeric elements.)

通过用最小距离分类判别方法，用MATLAB程序找出最小距离分类判别时的识别界面，从而进行识别已知的两类训练样本，并分析其识别错误率。(By using minimum distance classifier discriminant method, using MATLAB program to find the minimum distance classifier recognition interface when the judge, which is known to identify the two types of training samples, and analyze the recognition error rate.)

this example exchanges the NRZ code to the MANCHESTER code with moore output