SNRloss

opnet的培训课件，三天的培训内容，包括了概念介绍，建模，调试，以及两个实例。(opnet training courseware, training days, including the introduction, modeling, testing, and two examples.)

通过为MatLab添加标定工具箱，实现相机标定功能(By adding the calibration for the MatLab toolbox to achieve camera calibration function)

matlab程序运行时导入数据文件作为输入参数，三相光伏逆变并网的仿真，BP神经网络的整个训练过程。( Import data files as input parameters matlab program is running, Three-phase photovoltaic inverter and network simulation, The entire training process BP neural network.)

说明：  说明了matlab与cuda之间的关系，对于有一定基础的matlab编程人员来说，是一个可以借鉴的书(Matlab and cuda illustrates the relationship between the basis for some of the matlab programmers is a reference book)

附件里面是三相光伏模型，pq控制，大家共享(Three phase photovoltaic model, PQ control, we share)

加速度时程曲线通过matlab经过频域积分变换为位移时程曲线(Acceleration time history curve matlab integral transformation of the frequency domain through the process curve displacement)

为了精准、稳定地提取滚动轴承故障特征，提出了基于变分模态分解和奇异值分解的特征提取方法，采用标准模糊C均值聚类(fuzzy C means clustering, FCM)进行故障识 别。对同一负荷下的已知故障信号进行变分模态分解，利用 奇异值分解技术进一步提取各模态特征，通过FCM形成标准聚类中心，采用海明贴近度对测试样本进行分类，并通过计算分类系数和“卜均模糊嫡对分类性能进行评价，将该方法 应用于滚动轴承变负荷故障诊断。通过与基于经验模态分解的特征提取方法对比，该方法对标准FCM初始化条件小敏感，在同负荷故障诊断中表现出更好的分类性能 变负荷故障诊断时，除外圈故障特征线发生明显迁移，其他测试样本故障特征线仍在原聚类中心附近，整体故障识别率保持在100 ，因此，该方法能精确、稳定提取故障特征，为实际滚动轴承智能故障诊断提供参考。( In order to extract fault features of rolling bearing precisely and steadily, a method which is based on variational mode decomposition(VMD) and singular value decomposition was proposed for fault diagnosis using standard fuzzy C means clustering(FCM). First of all, the known fault signals measured in the same load but with different faults were decomposed by VMD, and the modes characteristics were further extracted using singular value decomposition technique,forming the standard clustering centers by FCM, and then the test samples were clustered by a Hamming nearness approach, and the classification performance was uated by calculating classification coefficient and average fuzzy entropy. At last, the method was applied in rolling bearing fault diagnosis under variable loads. By comparing with a method based on EMD, this approach is not sensitive to the initialization of standard FCM, and exhibits better classification performance in the same load fault diagnosis Fo)

说明：  SVPWM仿真，在matlab里面画的仿真图，可以参考参考，学习学习。(SVPWM simulation, the simulation in matlab figure inside the painting, see reference, learning to learn.)

在图像中处理椒盐噪声的自适应滤波器 代码原创(In the image processing salt &pepper noise adaptive filter)

Gauss 消元法 — 不选主元 Gauss 消元法 — 列选主元. 插值法 lagrange .cpp 插值法 lagrange .cpp 二分法.txt 二分法和简单迭代法以及埃特金.txt 复化辛卜生公式.txt快速弦截法 gauss-seidel选代.txt牛顿迭代法.txt(Gauss elimination method- do not choose the principal component Gauss elimination method- principal component out how. Interpolation lagrange. Cpp interpolation lagrange. Cpp dichotomy. Txt dichotomy and a simple iterative method, and Aitken. Txt Fu Xin Bo' s formula of . txt fast chord intercept method gauss-seidel iteration. txt Newton iterative method. txt)