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digital image processing book

均匀分布的微分熵。拉普拉斯分布的微分熵。独立成分分析的例题。(Uniform distribution of the differential entropy. The Laplace differential entropy distribution. Independent component analysis examples.)

matlab实现的深度学习代码，autocode(a code for deeplearing,autocode)

fcm实现简单的数值分类，只要你重新定义数据矩阵，就可以直接进行分类。(FCM implements simple numerical classification, which can be directly classified as long as you redefine the data matrix.)

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)

关于数字带通滤波器的编码matlab程序。可以作为函数直接引用。(Digital bandpass filter encoding matlab program. As a function reference.)

CDMA移动通信系统功率控制算法的MATLAB仿真实现(CDMA mobile communication system power control algorithm realize the MATLAB simulation)

MATLAB及在电子信息课程中的应用天线模型(antenna___em_modeling)

MATLAB® is a high-level technical computing language and interactive environment for algorithm development, data visualization, data analysis, and numeric computation. Using the MATLAB product, you can solve technical computing problems faster than with traditional programming languages, such as C, C++, and Fortran.You can use MATLAB in a wide range of applications, including signal and image processing, communications, control design, test and measurement, financial modeling and analysis, and computational biology. Add-on toolboxes (collections of special-purpose MATLAB functions, available separately) extend the MATLAB environment to solve particular classes of problems in these application areas.MATLAB provides a number of features for documenting and sharing your work. You can integrate your MATLAB code with other languages and applications, and distribute your MATLAB algorithms and applications.

链路预测的matlab实验源代码，通过这些源代码可以得出链路预测的基本实验效果(Link prediction matlab experiment source code, the source code can be obtained through these basic experimental results link prediction)