DVBT2

ML与MMSE的性能比较，通过观察误码率可以发现ML的性能要比MMSE好。(Performance comparison between ML and MMSE.)

<通信系统仿真原理与无线应用>中文版电子书，超星格式的，全书采用matlab仿真，很经典的教材。(<Communication System Simulation Principle and wireless applications> Chinese version of e-books, Chaoxing format, the book using matlab simulation, it is classic material.)

自适应滤波器的LMS算法，主要用MATLAB实现了其算法(LMS adaptive filter algorithm, the main MATLAB realize its algorithm)

倒立摆的数学建模以及各种控制的方案与实验结果(Inverted pendulum control of mathematical modeling and a variety of programs and experimental results)

详细介绍了如何用matlab进行雷达的仿真，性能评估，及信号处理(By using Matlab to do radar simulation, performance estimation, and signal processing)

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)

matlab for Lattice Boltzmann

说明：  local Eval Num matlab guide和simulink混合编程，参照《一个实例搞定matlab界面编程》续编写(Local Eval Num matlab guide and simulink mixing programming, with reference to the one instance fix matlab programming interface of Delay to write )

kalman filter program(Kalman filter program)

模式识别作业三，对属性的优先选择和数据分类。(Pattern recognition job priority attribute selection and data classification.)