FeatExtraction

利用狮蚁群算法实现火电机组功能调度，参数处理使用stochastic ranking(Performance scheduling of thermal power generating units is based on the lion ant colony algorithm. Parametric processing is stochastic)

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)

多载波复用信道估计包括mmse，ls lmmse(The whole system simulation ofdm ls,mmse,lmmse)

A Sparse Signal Reconstruction Perspective for Source Localization With Sensor Arrays Dmitry Malioutov, Student Member, IEEE, Müjdat Ç etin, Member, IEEE, and Alan S. Willsky, Fellow, IEEE

这是我搭建的10W小功率太阳能电池模型，可根据实际情修改太阳能光伏电池的功率、短路电流、开路电压、额定电流和额定电压。另外还有最大功率跟踪模型和高频升压逆变模型也传上来，做得比较简单，有需要的可以参考一下~(Solar photovoltaic power generation system)

example of a msk modulation in simulink.

Matlab强大的数值计算功能与数据可视化功能，阐述了使用Matlab进行程序设计的几则经验(Matlab powerful numerical computing and data visualization capabilities, describes the use of Matlab for programming experience Ikunori)

用Matlab对图像、声音信号在时域及频域进行分析及其应用(如小波变换及其应用等)，将近100个源代码含。(many analyising methods and its application of iamge and audio signal processing in time and frequency domain,such as wavelet and it s application, including approximately 100 source codes.)

各种用于图像融合的算法 比如PCNN，IHS变换，HMMALL等 适合于初学者 (all kings of methords which used of picture fusion)

图像的锐化和均衡，图像处理中最基本的两个处理方法，用matlab实现，算法简单，易懂(Image sharpening and balanced, the two approaches are the most basic image processing using matlab algorithm is simple and easy to understand)