MIMO雷达波束形成

this is the implementation of introduced algorithm(feature selection algorithm for mixed data with both nominal and continuous features,Wenyin Tang & K.Z. Mao)

以时滞切换系统为对象，给出了使系统稳定的输出状态反馈器设计条件(Dynamic output feedback control for a class of switched delay)

在matlab中实现峰值信噪比的函数 function y=psnr(im1,im2) 计算峰值信噪比程序——————————————— - ininput im1 : the original image matrix (For peak signal to noise ratio in matlab function function y = psnr (im1, im2) calculated PSNR program)

说明：  analysis of ber in fbmc and ofdm

一维信号的小波分解和重构，利用小波变换对一维声音信号进行分解和重构(One-dimensional signal wavelet decomposition and reconstruction, using wavelet transform one-dimensional sound signal decomposition and reconstruction)

针对非圆信号DOA估计问题,提出了一种基于实值特征值分解 (Eigenvalue decomposition,EVD)的求根MUSIC算法.首先利用非圆信号为实值信号的特点,将阵列上的接收数据及其共轭用欧拉公式转换为实值正弦与 余弦数据,然后将正弦与余弦数据进行串联,从而扩展了数据维数.由于采用实值矩阵的EVD,因此在EVD阶段的运算量简化为复值EVD的1/4.根据 EVD后获得的信号与噪声子空间的特点,对噪声子空间和导向矩阵进行重构以便于可以使用求根MUSIC算法获取对DOA的估计.仿真实验验证了本文算法的 有效性(For the estimation of noncircular signals of DOA, proposes a decomposition value based on real valued features (Eigenvalue decomposition, EVD) the root MUSIC algorithm. Firstly, characteristics of non circular signals for real valued signals, the array data and its conjugate with the Euler formula into real value of sine and cosine and sine and cosine data. The data series, thus expanding the dimension of the data. Because of the use of real valued matrix computation in EVD, so the EVD stage was simplified as a complex valued EVD 1/4. according to the characteristics of signal and noise subspace is obtained after EVD, the noise subspace and orientation matrix reconstruction in order to facilitate the use of DOA can obtain the estimated root MUSIC the algorithm. The simulation results verify the effectiveness of the proposed algorithm)

支持向量机，用于分类，含训练集与测试集，用SVM进行多分类(Support Vector Machine (SVM), used for classification, including training set and test set, and multi-support vector machine (SVM))

说明：  上传一份MSA的MATLAB代码示例，希望能有帮助(Upload an example of MSA's MATLAB code, hoping to help)

this code can segment class using kmeans

卡尔曼滤波理论和实践，第三版，经典书籍，值得参考(Kalman filtering theory and practice, third edition, classic books, it is also useful)