Digitalsignalprocessingcourseware

数值分析的非线性方程组的解法，工具使用的是matlab，很简单但很实用。(Numerical analysis of nonlinear equations, solution, tool use matlab, very simple but very practical.)

Component example backup with MyDac library

AR模型参数BURG算法估计的功能函数及源代码(BURG AR model parameter estimation algorithm performance function and source code)

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)

一个混沌信号产生器MATLAB源代码。主要用于产生混沌信号序列。()

simulation mode glissant

双馈感应风力发电机的模型，矢量控制，定子电压定向，完全自己搭建(Doubly fed induction wind generator model, vector control, the stator voltage oriented, to build their own completely)

雷达系统仿真，模拟接收信号同噪声叠加过程(Simulate the operation in a radar communication system. Delay of the recieving signal and the noise addition is demonstrated.)

RTL8201 circuit application

it is a code for machine vision