dwh_source

QAM modulation and demodulation,qpsk modulation and demodulation

该文档里面包含了MATLAB里常用的命令及例子，介绍的非常详细。(The document which contains a MATLAB command that is commonly used and examples described in great detail.)

自己编写的BDPSK调制与解调，内含matlab-figure-file、matlab-M-file和得出的jpg格式图形！(I have written BDPSK modulation and demodulation, containing matlab-figure-file, matlab-M-file and come to the jpg format graphics!)

基于奇异值分解的图像压缩。分别给出了灰度及RGB真彩图的压缩代码。　　 (Based on singular value decomposition of the image compression. Are given respectively grayscale and RGB true color pictures of the compression code.)

说明：  通过非线性动力学中混沌研究的poincare图可以很方便的识别出周期，拟周期或者混沌运动，该程序实现了poincare图的绘制(Through the study of nonlinear dynamics in the chaotic poincare map can easily identify periodic, quasi-periodic or chaotic motion, the program achieved poincare mapping)

说明：  莱斯利人口预测模型 莱斯利矩阵为91阶方针表示从0岁到90岁各个年龄段的生育率和存活率集合(leslie )

PHD 滤波器，用于多目标跟踪，很实用的方法(PHD fliter)

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)

混沌序列发生器，一种随机序列的预测！时间序列的分析和预测！(Chaotic sequence generator, a random sequence of the forecast! Time series analysis and forecasting!)

一个采用Matlab编写的设计FIR滤波器的教程和源代码，便于新手学习设计滤波器和数字信号处理。(a Matlab design prepared by the FIR filter guide and source code, newcomers to facilitate learning how to design filters and digital signal processing.)