zhidonghuihui

this is good codes from a typical book

提取故障发生时正向行波和反向行波的示例程序,本程序计算的是0模分量,设定仿真模型在0.035s时发生故障,故障分量取为从故障后的0.035s~0.039s减去故障前的0.015s~0.019s(Forward traveling wave and reverse traveling wave sample program to extract a fault occurs, the program calculates the 0-mode component, set the simulation model in 0.035s failure, the fault component is taken as from the failure 0.035s ~ 0.039s less before the failure 0.015s ~ 0.019s)

很好的MATLAB学习资料，简单易懂，希望对大家有所帮助，！(good works！)

基于二值数据的贝叶斯分类器，用于数字识别(Based on binary data Bayesian classifier)

Cross Validation in Matlab 2011

连续相位信号调制解调，CPM全响应信号调制解调( Continuous phase signal modulation and demodulation, CPM full response signal modulation and demodulation)

基于压缩感知的语音压缩与重构.PDF(Compression and Reconstruction of Speech Signal Based on Compressed Sensing)(Compression and Reconstruction of Speech Signal Based on Compressed Sensing )

卷积码编码及其维特比译码matlab实现(Convolutional coding and Viterbi decoding matlab implementation)

说明：  提出的方法(DC-ADMM-P)采用了一种新的策略，即使用consensus ADMM来解决DC-DOPF-CET的对偶问题，而只揭示相邻子系统之间的边界分支信息。此外，通过减少双乘子的误码率和采用改进的乘子更新步骤，提高了DC-ADMM-P的收敛性能。(the ADMM-based distributed approaches disclose boundary buses and branches information among adjacent subsystems. As opposed to these methods, the proposed method (DC-ADMM-P) adopts a novel strategy which uses consensus ADMM to solve the dual of DC-DOPF-CET while only disclose boundary branches infor-mation among adjacent subsystems. Moreover, the convergence performance of DC-ADMM-P is improved by reducing the num-ber of dual multipliers and employing an improved update step of the multiplier.)

12.1 图像点的运算 12.1.1 线性点运算 12.1.2 非线性点运算 12.2 图像的算术运算 12.2.1 加法运算 12.2.2 减 法运算 12.2.3 乘法 运算 12.2.4 除法 运算 12.2.5 其它运算 12.3 图像的位逻辑运算 12.4 图像的几何运算 12.4.1 图像插值 12.4.2 图像缩放 12.4.3 图像旋转 12.4.4 图像剪切 12.5 空间变换 12.5.1 仿射变换（ affine transformation ） 12.5.2 透视变换 (Perspective Transformation) 12.5.3 空间变换的 MATLAB 函数 12.5.4 空间变换实例 12.6 图像融合 12.7 邻域与块操作 12.7.1 邻域操作 12.7.2 图像块操作 12.8 区域处理 12.8.1 区域选择 12.8.2 区域滤波 12.8.3 区域填充(12.1 image point arithmetic 12.1.1 computing linear point 12.1.2 nonlinear point operations 12.2 image adder computing 12.2.1 Arithmetic 12.2.2 subtraction multiplication 12.2.3 computing division 12.2.4 computing 12.2.5 other computing 12.3 Image 12.4 Image-bit logic operations geometric computing 12.4.1 Image Interpolation 12.4.2 image scaling 12.4.3 image rotation 12.4.4 Shear Image 12.5 Space Conversion 12.5.1 affine transformation (affine transformation) 12.5.2 Perspective Transform (Perspective Transformation) 12.5.3 space transform space transform MATLAB function 12.5.4 Examples 12.6 Image Fusion 12.7 Neighborhood and Block Operation 12.7.1 Operation 12.7.2 neighborhood image processing block operation 12.8 Regional 12.8 area selection 12.8.1. 2 regional filtering area filling 12.8.3)