CRITIC模型计算权重

PN_GEN: This is a matlab function generates the Pseudo Noise sequnece of length (N)according to Generation Polynom and input state. Inputs: G - Generation Polynom, Zin - Initial state of Shift register N - The length of PN sequence Outputs: y - The resulting PN sequence Z - The output state of Shift register

Implementing the Belief Propagation Algorithm in MATLAB

基于Matlab和ActiveX技术的数字信号处理教学演示系统(Matlab based on ActiveX technology and digital signal processing teaching demonstration system)

matlabr软件应用的图形图像处理，很专业的教材，事例很多(matlabr graphic image processing software applications, very professional materials, many examples)

流体力学方法模拟单离子一维鞘层的matlab代码，可作为交流学习使用(Fluid dynamics simulation of a single one-dimensional ion sheath matlab code, can be used as learning to use exchange)

BP与GA-BP算法用于温度补偿函数拟合的比较(For the comparison of temperature compensation function fitting BP and GA-BP algorithm)

说明：  列与约束算法解决鲁棒经济调度问题，分解成主问题和子问题解决(Column and constraint algorithms solve the robust economic scheduling problem,which are decomposed into main problems and sub-problems)

Homomorphic filter for image processing

选择两张图片，一张水印图，一张嵌入图，将水印图进行Arnold置乱算法将其置乱，嵌入到嵌入图中，形成数字零水印，选用白噪声、高斯低通滤波、压缩、剪切、旋转攻击测试。以此观察图像鲁棒性(Select two pictures, a watermark and an embedded graph. We will scramble the watermark image with Arnold scrambling algorithm and embed it into the embedded map to form digital zero watermark. We choose white noise, Gauss low pass filtering, compression, shearing and rotation attack test. To observe the robustness of the image)

先归一化输入输出参数，用KMens优化RBF神经网络中心值，然后计算隐节点数据中心间的距离（矩阵），得到各隐节点的扩展常数（宽度），接着用最小二乘法得到各隐节点的输出权值，对数据进行反归一化，并绘图得到神经网络输出与测试集图，同时进行性能评价(First, the input and output parameters are normalized, the central value of the RBF neural network is optimized by KMens, then the distance (matrix) between the data centers of the hidden nodes is calculated, and the extended constant (width) of the hidden nodes is obtained. Then the output weights of the hidden nodes are obtained by the least square method, and the data are back normalized, and the neural network is drawn. Output and test set diagrams, and performance evaluation)