robot-9.8

this code is for REAL-valued signals. An implementation of JADE for both real and complex signals is also available from http://perso.telecom-paristech.fr/~cardoso/guidesepsou.html

通过matlab实现数据的时域图D代码呵呵呵呵(When implementing data via matlab domain map)

matlab的工具箱的安装步骤： 1.解压下载的文件包，将tft/mfile复制到matlab的toolbox文件夹下 2.建立搜索路径，matlab->file->Set Path->Add Folder ->选择mfile文件夹复制到matlab的toolbox的路径->save->close 3.测试是否建立搜索路径成功，在matlab命令窗口打入：which fmsin 返回的结果是你放mfile的正确路径说明建立搜索路径成功。此时就完成了安装工具包的工作。 (matlab toolbox installation steps: 1. decompress the downloaded file package, which will tft/mfile matlab' s toolbox copy to folder 2. to establish the search path, matlab-> file-> Set Path-> Add Folder-> Select matlab mfile folder to the path of the toolbox-> save-> close 3. test whether the establishment of a successful search path, in the matlab command window enter: which fmsin return mfile result is you put the correct path to search path that create success. At this point the installation kit to complete the work.)

为了得到具有一般相关量测噪声线性系统的递推滤波算法, 将该问题转化为具有相关量测 单值随机向量的滤波问题,根据单值随机向量的线性无偏最小方差估计算法,导出了量测噪声为一 般相关鞅差序列的线性系统的最优递推状态估计滤波算法.通过数值仿真,将该算法与假定量测噪 声不相关时的Kalman 滤波算法进行了比较,证明了该算法的有效性(In order to obtain the recursive f i ltering alg orithm for a linear system w ith general correlat
ed measurement noises, the problem is t ransformed to that of filtering for a single random vector w ith correlated measurements. According to the linear unbiased minimum variance estimation algorithm for a single random vector, a recursive filtering algori thm is presented. A digital simulat ion technique is used such that the new algorithm can be compared w i th the Kalman f i ltering algorithm, assuming that the measurement noises are uncorrelated. Validi ty of the proposed algorithm is thus proved)

基于GMM说话人识别特征提取 1、需要有语音工具箱 2、训练和测试包含了加噪的代码 3、包含噪声数据 4、没有包含语音数据 5、语音数据可以自行录制或者找一段语音(Extraction Based on GMM speaker recognition feature A need to have a voice toolbox 2, the training and testing included adding noise code 3, including noise data 4, does not contain voice data 5, the voice data can be recorded on their own or find a voice)

基于LMS.MVDR的波束形成函数库，并有例子说明。(beamforming1)

一种智能优化算法-带交叉因子的粒子群优化算法(With cross factor particle swarm)

去除图像因为运动、噪声而产生的模糊,使用方法：维纳滤波、直接逆滤波、L-R迭代(Remove the fuzzy of image generated by movement, noise)

57节点潮流计算代码,能够显示出潮流计算结果，输入renfp（‘case57’）即可(57 node flow calculation code, can show the flow calculation results, enter renfp (' case57' ) can be)

gmcalab 快速广义的形态分量分析，基于K均值的PSO聚类算法,PLS部分最小二乘工具箱。( gmcalab fast generalized form component analysis, K-means clustering algorithm based on the PSO, PLS PLS toolbox.)