unsat2d

基于数值计算的矩阵分解。用MATLAB实现的LU分解算法(Based on the numerical calculation of decomposing matrix. MATLAB LU decomposition algorithm)

This file gives the Ground Tracks of a Geostationary satellite

QAM generation par matlab

说明：  该程序主要也是针对滤波器设计的，实现了对一个语音信号的滤波处理(The program is largely designed for the filter, the realization of a voice signal filtering)

autre methode couple generatrice asychrone

这是有关机器人的一个matlab代码，相信着应该对机器人专业的同学会有用！(It is about a robot matlab code, I believe that the students should be useful robot professional!)

局部约束的软编码程序,可用于图像分类,效果非常好.(local-soft-assignment coding,it can be used to classify images)

用于车牌识别技术中图像分割，对比几种微分算子的边缘检测和形态学分割(License plate recognition technology for image segmentation, compared to several differential operator edge detection and morphological segmentation)

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)

pid control tuning process through matlab. very simple using BPN.