STBC

一个维纳滤波算法,利用MATLAB编写的,解压后可直接调用(a Wiener filter algorithm, using MATLAB, unpacked directly call)

实现MATLAB的自适应滤波器代码，LMS的改进，分析其收敛性(MATLAB realization)

pso coding in matlab

说明：  一种FxLMS自适应滤波算法 LMS自适应滤波算法RLS自适应滤波算法变换域自适应滤波算法仿射投影算法共扼梯度算法基于子带分解的自适应滤波算法基于QR分解的自适应滤波算法算法性能评价变步长的自适应滤波算法时变系统跟踪速度与收敛精度方面对算法调整步长因子u的矛盾,但变步长中的其它参数的选取还需实验来确定,应用起来不太方便。对RLS算法的各种改进,其目的均是保留RLS算法收敛速度快的特点而降低其计算复杂性。变换域类算法亦是想通过作某些正交变换使输入信号自相关矩阵的特征值发散程度变小,提高收敛速度。而仿射投影算法的性能介于LMS算法和RLS算法之间。共扼梯度自适应滤波算法的提出是为了降低RLS类算法的复杂性和克服某些快速RLS算法存在的数值稳定性问题。信号的子带分解能降低输入信号的自相关矩阵的特征值发散程度,从而加快自适应滤波算法的收敛速度,同时便于并行处理,带来了一定的灵活性。(A FXLMS adaptive filtering algorithm)

产生一个连续信号，包含低频，中频，高频分量，对其进行采样，进行频谱分析，分别设计三种高通，低通，带通滤波器对信号进行滤波处理，观察滤波后信号的频谱。(generating a continue time singal,which contains low,middle and high frequences,sampling it.analisize its spetrum.Then designing three kind filters are lowpass,highpass,bandpass filters and processing it.Observing its spetrum.)

此内容是电气工程及其自动化专业毕业设计中 所能用到得MATLAB仿真(This content is graduated in electrical engineering and automation design can be used in MATLAB simulation)

沈阳航空航天大学电子信息工程 语音信号处理电子版指导书。。内有大量语音信号源程序，可供参考(Shenyang Aerospace Electronics and Information Engineering University of speech signal processing electronic version of the guide book. . There are a large number of audio signal source, available for reference)

代码1用于将位置经纬高信息转换为地心地固坐标系下xyz信息；代码2是捷联惯导算法代码，用于将加速度计和陀螺仪输出的信息进行解算得到位置、速度和姿态信息。(Code 1 is used to convert the location of warp and weft information into XYZ information in a geocentric coordinate system; code 2 is a strapdown inertial navigation algorithm code, which is used to compute the information of accelerometers and gyroscopes to get position, speed and attitude information.)

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)

uses partial correlation function and filter to implement an AR model